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DICE: Leveraging Sparsification for Out-of-Distribution Detection | 25 | eccv | 6 | 0 | 2023-06-17 00:59:09.612000 | https://github.com/deeplearning-wisc/dice | 30 | Dice: Leveraging sparsification for out-of-distribution detection | https://scholar.google.com/scholar?cluster=878626789575390648&hl=en&as_sdt=0,33 | 3 | 2,022 |
Invariant Feature Learning for Generalized Long-Tailed Classification | 12 | eccv | 8 | 2 | 2023-06-17 00:59:09.823000 | https://github.com/kaihuatang/generalized-long-tailed-benchmarks.pytorch | 99 | Invariant feature learning for generalized long-tailed classification | https://scholar.google.com/scholar?cluster=2921674289381974673&hl=en&as_sdt=0,5 | 2 | 2,022 |
Sliced Recursive Transformer | 12 | eccv | 10 | 0 | 2023-06-17 00:59:10.035000 | https://github.com/szq0214/sret | 55 | Sliced recursive transformer | https://scholar.google.com/scholar?cluster=6881440757906382227&hl=en&as_sdt=0,11 | 6 | 2,022 |
Cross-Domain Ensemble Distillation for Domain Generalization | 3 | eccv | 5 | 1 | 2023-06-17 00:59:10.249000 | https://github.com/leekyungmoon/XDED | 20 | Cross-domain Ensemble Distillation for Domain Generalization | https://scholar.google.com/scholar?cluster=7614016061271891852&hl=en&as_sdt=0,5 | 4 | 2,022 |
Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels | 2 | eccv | 2 | 3 | 2023-06-17 00:59:10.462000 | https://github.com/uitrbn/tscsi_idn | 8 | Centrality and consistency: two-stage clean samples identification for learning with instance-dependent noisy labels | https://scholar.google.com/scholar?cluster=17182529425583795058&hl=en&as_sdt=0,5 | 1 | 2,022 |
VL-LTR: Learning Class-Wise Visual-Linguistic Representation for Long-Tailed Visual Recognition | 15 | eccv | 10 | 6 | 2023-06-17 00:59:10.674000 | https://github.com/ChangyaoTian/VL-LTR | 51 | Vl-ltr: Learning class-wise visual-linguistic representation for long-tailed visual recognition | https://scholar.google.com/scholar?cluster=3647078390700500997&hl=en&as_sdt=0,32 | 3 | 2,022 |
Class Is Invariant to Context and Vice Versa: On Learning Invariance for Out-of-Distribution Generalization | 3 | eccv | 0 | 0 | 2023-06-17 00:59:10.890000 | https://github.com/simpleshinobu/irmcon | 16 | Class is invariant to context and vice versa: on learning invariance for out-of-distribution generalization | https://scholar.google.com/scholar?cluster=10029134243700219683&hl=en&as_sdt=0,5 | 0 | 2,022 |
Hierarchical Semi-Supervised Contrastive Learning for Contamination-Resistant Anomaly Detection | 2 | eccv | 1 | 0 | 2023-06-17 00:59:11.105000 | https://github.com/gaoangw/hscl | 7 | Hierarchical Semi-supervised Contrastive Learning for Contamination-Resistant Anomaly Detection | https://scholar.google.com/scholar?cluster=13983761419031899211&hl=en&as_sdt=0,31 | 1 | 2,022 |
RealPatch: A Statistical Matching Framework for Model Patching with Real Samples | 1 | eccv | 0 | 0 | 2023-06-17 00:59:11.321000 | https://github.com/wearepal/realpatch | 2 | RealPatch: A Statistical Matching Framework for Model Patching with Real Samples | https://scholar.google.com/scholar?cluster=16389603249076638788&hl=en&as_sdt=0,33 | 2 | 2,022 |
Semantic Novelty Detection via Relational Reasoning | 0 | eccv | 0 | 0 | 2023-06-17 00:59:11.534000 | https://github.com/francescocappio/resend | 14 | Semantic Novelty Detection via Relational Reasoning | https://scholar.google.com/scholar?cluster=2885314653619622739&hl=en&as_sdt=0,5 | 1 | 2,022 |
Training Vision Transformers with Only 2040 Images | 14 | eccv | 4 | 2 | 2023-06-17 00:59:11.745000 | https://github.com/CupidJay/Training-Vision-Transformers-with-only-2040-images | 43 | Training vision transformers with only 2040 images | https://scholar.google.com/scholar?cluster=15808243844725790365&hl=en&as_sdt=0,31 | 2 | 2,022 |
TDAM: Top-Down Attention Module for Contextually Guided Feature Selection in CNNs | 3 | eccv | 0 | 0 | 2023-06-17 00:59:11.957000 | https://github.com/shantanuj/tdam_top_down_attention_module | 6 | TDAM: Top-Down Attention Module for Contextually Guided Feature Selection in CNNs | https://scholar.google.com/scholar?cluster=10902957044896292324&hl=en&as_sdt=0,44 | 1 | 2,022 |
Automatic Check-Out via Prototype-Based Classifier Learning from Single-Product Exemplars | 1 | eccv | 0 | 2 | 2023-06-17 00:59:12.190000 | https://github.com/hao-chen-njust/psp | 1 | Automatic Check-Out via Prototype-Based Classifier Learning from Single-Product Exemplars | https://scholar.google.com/scholar?cluster=9346886979579970159&hl=en&as_sdt=0,5 | 1 | 2,022 |
Overcoming Shortcut Learning in a Target Domain by Generalizing Basic Visual Factors from a Source Domain | 1 | eccv | 0 | 0 | 2023-06-17 00:59:12.402000 | https://github.com/boschresearch/sourcegen | 1 | Overcoming Shortcut Learning in a Target Domain by Generalizing Basic Visual Factors from a Source Domain | https://scholar.google.com/scholar?cluster=11823647734753043783&hl=en&as_sdt=0,5 | 3 | 2,022 |
Wave-ViT: Unifying Wavelet and Transformers for Visual Representation Learning | 28 | eccv | 21 | 6 | 2023-06-17 00:59:12.620000 | https://github.com/yehli/imagenetmodel | 109 | Wave-vit: Unifying wavelet and transformers for visual representation learning | https://scholar.google.com/scholar?cluster=9894263145711509588&hl=en&as_sdt=0,5 | 5 | 2,022 |
Tailoring Self-Supervision for Supervised Learning | 5 | eccv | 3 | 0 | 2023-06-17 00:59:12.833000 | https://github.com/wjun0830/localizable-rotation | 19 | Tailoring Self-Supervision for Supervised Learning | https://scholar.google.com/scholar?cluster=7286213705306968536&hl=en&as_sdt=0,33 | 4 | 2,022 |
Difficulty-Aware Simulator for Open Set Recognition | 5 | eccv | 2 | 0 | 2023-06-17 00:59:13.046000 | https://github.com/wjun0830/difficulty-aware-simulator | 24 | Difficulty-Aware Simulator for Open Set Recognition | https://scholar.google.com/scholar?cluster=13965399748614059565&hl=en&as_sdt=0,5 | 1 | 2,022 |
Few-Shot Class-Incremental Learning from an Open-Set Perspective | 14 | eccv | 3 | 0 | 2023-06-17 00:59:13.259000 | https://github.com/canpeng123/fscil_alice | 19 | Few-Shot Class-Incremental Learning from an Open-Set Perspective | https://scholar.google.com/scholar?cluster=16116173187693664231&hl=en&as_sdt=0,47 | 2 | 2,022 |
FOSTER: Feature Boosting and Compression for Class-Incremental Learning | 34 | eccv | 0 | 2 | 2023-06-17 00:59:13.471000 | https://github.com/G-U-N/ECCV22-FOSTER | 31 | Foster: Feature boosting and compression for class-incremental learning | https://scholar.google.com/scholar?cluster=17421080525009780737&hl=en&as_sdt=0,33 | 3 | 2,022 |
Visual Knowledge Tracing | 0 | eccv | 1 | 0 | 2023-06-17 00:59:13.685000 | https://github.com/nkondapa/visualknowledgetracing | 13 | Visual Knowledge Tracing | https://scholar.google.com/scholar?cluster=17421247468685964476&hl=en&as_sdt=0,8 | 1 | 2,022 |
Improving Fine-Grained Visual Recognition in Low Data Regimes via Self-Boosting Attention Mechanism | 3 | eccv | 4 | 7 | 2023-06-17 00:59:13.899000 | https://github.com/ganperf/sam | 19 | Improving fine-grained visual recognition in low data regimes via self-boosting attention mechanism | https://scholar.google.com/scholar?cluster=1093309124842032174&hl=en&as_sdt=0,5 | 3 | 2,022 |
VSA: Learning Varied-Size Window Attention in Vision Transformers | 25 | eccv | 6 | 5 | 2023-06-17 00:59:14.113000 | https://github.com/vitae-transformer/vitae-vsa | 132 | VSA: learning varied-size window attention in vision transformers | https://scholar.google.com/scholar?cluster=7134900495559356797&hl=en&as_sdt=0,5 | 2 | 2,022 |
DenseHybrid: Hybrid Anomaly Detection for Dense Open-Set Recognition | 14 | eccv | 3 | 2 | 2023-06-17 00:59:14.326000 | https://github.com/matejgrcic/DenseHybrid | 20 | Densehybrid: Hybrid anomaly detection for dense open-set recognition | https://scholar.google.com/scholar?cluster=17117872304717676783&hl=en&as_sdt=0,36 | 2 | 2,022 |
Rethinking Confidence Calibration for Failure Prediction | 7 | eccv | 1 | 0 | 2023-06-17 00:59:14.542000 | https://github.com/impression2805/fmfp | 13 | Rethinking Confidence Calibration for Failure Prediction | https://scholar.google.com/scholar?cluster=3192244699956049091&hl=en&as_sdt=0,5 | 2 | 2,022 |
Uncertainty-Guided Source-Free Domain Adaptation | 14 | eccv | 3 | 2 | 2023-06-17 00:59:14.759000 | https://github.com/roysubhankar/uncertainty-sfda | 31 | Uncertainty-guided source-free domain adaptation | https://scholar.google.com/scholar?cluster=10598112265751424023&hl=en&as_sdt=0,44 | 4 | 2,022 |
Should All Proposals Be Treated Equally in Object Detection? | 0 | eccv | 1 | 0 | 2023-06-17 00:59:14.974000 | https://github.com/liyunsheng13/dpp | 31 | Should All Proposals Be Treated Equally in Object Detection? | https://scholar.google.com/scholar?cluster=12493352248493160142&hl=en&as_sdt=0,24 | 6 | 2,022 |
PRIME: A Few Primitives Can Boost Robustness to Common Corruptions | 12 | eccv | 5 | 1 | 2023-06-17 00:59:15.192000 | https://github.com/amodas/PRIME-augmentations | 38 | PRIME: A few primitives can boost robustness to common corruptions | https://scholar.google.com/scholar?cluster=4562095737228687677&hl=en&as_sdt=0,11 | 3 | 2,022 |
In Defense of Image Pre-training for Spatiotemporal Recognition | 0 | eccv | 0 | 1 | 2023-06-17 00:59:15.422000 | https://github.com/ucsc-vlaa/image-pretraining-for-video | 17 | In Defense of Image Pre-Training for Spatiotemporal Recognition | https://scholar.google.com/scholar?cluster=18269323448808190712&hl=en&as_sdt=0,33 | 0 | 2,022 |
Augmenting Deep Classifiers with Polynomial Neural Networks | 5 | eccv | 0 | 0 | 2023-06-17 00:59:15.636000 | https://github.com/grigorisg9gr/polynomials-for-augmenting-nns | 2 | Augmenting deep classifiers with polynomial neural networks | https://scholar.google.com/scholar?cluster=14218781642284557592&hl=en&as_sdt=0,5 | 2 | 2,022 |
Learning with Noisy Labels by Efficient Transition Matrix Estimation to Combat Label Miscorrection | 3 | eccv | 1 | 1 | 2023-06-17 00:59:15.849000 | https://github.com/hyperconnect/fasten | 6 | Learning with Noisy Labels by Efficient Transition Matrix Estimation to Combat Label Miscorrection | https://scholar.google.com/scholar?cluster=13055133803881493745&hl=en&as_sdt=0,5 | 7 | 2,022 |
Contrastive Deep Supervision | 7 | eccv | 3 | 1 | 2023-06-17 00:59:16.064000 | https://github.com/archiplab-linfengzhang/contrastive-deep-supervision | 50 | Contrastive deep supervision | https://scholar.google.com/scholar?cluster=7265954552843581197&hl=en&as_sdt=0,44 | 3 | 2,022 |
Discriminability-Transferability Trade-Off: An Information-Theoretic Perspective | 7 | eccv | 0 | 0 | 2023-06-17 00:59:16.281000 | https://github.com/dtennant/dt-tradeoff | 5 | Discriminability-transferability trade-off: an information-theoretic perspective | https://scholar.google.com/scholar?cluster=4648654949432885317&hl=en&as_sdt=0,33 | 1 | 2,022 |
LocVTP: Video-Text Pre-training for Temporal Localization | 22 | eccv | 0 | 4 | 2023-06-17 00:59:16.494000 | https://github.com/mengcaopku/locvtp | 34 | Locvtp: Video-text pre-training for temporal localization | https://scholar.google.com/scholar?cluster=12927720534552603420&hl=en&as_sdt=0,5 | 2 | 2,022 |
Learning Ego 3D Representation As Ray Tracing | 14 | eccv | 5 | 2 | 2023-06-17 00:59:16.712000 | https://github.com/fudan-zvg/ego3rt | 92 | Learning ego 3d representation as ray tracing | https://scholar.google.com/scholar?cluster=11031442758029473428&hl=en&as_sdt=0,33 | 12 | 2,022 |
Static and Dynamic Concepts for Self-Supervised Video Representation Learning | 3 | eccv | 1 | 1 | 2023-06-17 00:59:16.925000 | https://github.com/shvdiwnkozbw/Self-supervised-Video-Concept | 10 | Static and Dynamic Concepts for Self-supervised Video Representation Learning | https://scholar.google.com/scholar?cluster=2899262297077900123&hl=en&as_sdt=0,5 | 1 | 2,022 |
Hierarchically Self-Supervised Transformer for Human Skeleton Representation Learning | 8 | eccv | 2 | 1 | 2023-06-17 00:59:17.138000 | https://github.com/yuxiaochen1103/Hi-TRS | 18 | Hierarchically Self-supervised Transformer for Human Skeleton Representation Learning | https://scholar.google.com/scholar?cluster=17795536636846688217&hl=en&as_sdt=0,5 | 1 | 2,022 |
CoSCL: Cooperation of Small Continual Learners Is Stronger than a Big One | 3 | eccv | 2 | 0 | 2023-06-17 00:59:17.350000 | https://github.com/lywang3081/coscl | 12 | CoSCL: Cooperation of Small Continual Learners is Stronger Than a Big One | https://scholar.google.com/scholar?cluster=10311122253648677302&hl=en&as_sdt=0,41 | 1 | 2,022 |
Fast-MoCo: Boost Momentum-Based Contrastive Learning with Combinatorial Patches | 3 | eccv | 0 | 0 | 2023-06-17 00:59:17.562000 | https://github.com/orashi/fast-moco | 9 | Fast-MoCo: Boost Momentum-Based Contrastive Learning with Combinatorial Patches | https://scholar.google.com/scholar?cluster=3809897863505864658&hl=en&as_sdt=0,5 | 1 | 2,022 |
LoRD: Local 4D Implicit Representation for High-Fidelity Dynamic Human Modeling | 2 | eccv | 6 | 0 | 2023-06-17 00:59:17.774000 | https://github.com/BoyanJIANG/LoRD | 57 | LoRD: Local 4D Implicit Representation for High-Fidelity Dynamic Human Modeling | https://scholar.google.com/scholar?cluster=18207490584500698956&hl=en&as_sdt=0,10 | 4 | 2,022 |
On the Versatile Uses of Partial Distance Correlation in Deep Learning | 5 | eccv | 16 | 0 | 2023-06-17 00:59:17.986000 | https://github.com/zhenxingjian/partial_distance_correlation | 162 | On the versatile uses of partial distance correlation in deep learning | https://scholar.google.com/scholar?cluster=17295760961898440654&hl=en&as_sdt=0,38 | 4 | 2,022 |
DAS: Densely-Anchored Sampling for Deep Metric Learning | 4 | eccv | 1 | 0 | 2023-06-17 00:59:18.199000 | https://github.com/lizhaoliu-Lec/DAS | 14 | Das: Densely-anchored sampling for deep metric learning | https://scholar.google.com/scholar?cluster=13410935767802137885&hl=en&as_sdt=0,5 | 2 | 2,022 |
Learn from All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition | 31 | eccv | 8 | 5 | 2023-06-17 00:59:18.410000 | https://github.com/zyh-uaiaaaa/erasing-attention-consistency | 48 | Learn from all: Erasing attention consistency for noisy label facial expression recognition | https://scholar.google.com/scholar?cluster=3230431190406827600&hl=en&as_sdt=0,5 | 2 | 2,022 |
A Non-Isotropic Probabilistic Take On Proxy-Based Deep Metric Learning | 3 | eccv | 0 | 0 | 2023-06-17 00:59:18.623000 | https://github.com/explainableml/probabilistic_deep_metric_learning | 11 | A Non-isotropic Probabilistic Take on Proxy-based Deep Metric Learning | https://scholar.google.com/scholar?cluster=18270830460222491727&hl=en&as_sdt=0,5 | 8 | 2,022 |
TokenMix: Rethinking Image Mixing for Data Augmentation in Vision Transformers | 17 | eccv | 8 | 6 | 2023-06-17 00:59:18.841000 | https://github.com/sense-x/tokenmix | 85 | Tokenmix: Rethinking image mixing for data augmentation in vision transformers | https://scholar.google.com/scholar?cluster=8406088123118572709&hl=en&as_sdt=0,5 | 6 | 2,022 |
Sound Localization by Self-Supervised Time Delay Estimation | 6 | eccv | 5 | 0 | 2023-06-17 00:59:19.053000 | https://github.com/IFICL/stereocrw | 10 | Sound Localization by Self-Supervised Time Delay Estimation | https://scholar.google.com/scholar?cluster=13725278977691156575&hl=en&as_sdt=0,5 | 1 | 2,022 |
SLIP: Self-Supervision Meets Language-Image Pre-training | 163 | eccv | 61 | 18 | 2023-06-17 00:59:19.266000 | https://github.com/facebookresearch/slip | 672 | Slip: Self-supervision meets language-image pre-training | https://scholar.google.com/scholar?cluster=17384094251372134587&hl=en&as_sdt=0,5 | 16 | 2,022 |
A Contrastive Objective for Learning Disentangled Representations | 7 | eccv | 0 | 0 | 2023-06-17 00:59:19.478000 | https://github.com/jonkahana/dcodr | 4 | A contrastive objective for learning disentangled representations | https://scholar.google.com/scholar?cluster=17352506721201259151&hl=en&as_sdt=0,10 | 1 | 2,022 |
PT4AL: Using Self-Supervised Pretext Tasks for Active Learning | 4 | eccv | 2 | 6 | 2023-06-17 00:59:19.690000 | https://github.com/johnsk95/pt4al | 45 | PT4AL: Using Self-supervised Pretext Tasks for Active Learning | https://scholar.google.com/scholar?cluster=11229213520949185993&hl=en&as_sdt=0,5 | 5 | 2,022 |
DualPrompt: Complementary Prompting for Rehearsal-Free Continual Learning | 62 | eccv | 33 | 4 | 2023-06-17 00:59:19.902000 | https://github.com/google-research/l2p | 284 | Dualprompt: Complementary prompting for rehearsal-free continual learning | https://scholar.google.com/scholar?cluster=7069579101447184812&hl=en&as_sdt=0,10 | 7 | 2,022 |
Joint Learning of Localized Representations from Medical Images and Reports | 20 | eccv | 3 | 0 | 2023-06-17 00:59:20.114000 | https://github.com/philip-mueller/lovt | 12 | Joint learning of localized representations from medical images and reports | https://scholar.google.com/scholar?cluster=9049923034415496270&hl=en&as_sdt=0,31 | 1 | 2,022 |
Identifying Hard Noise in Long-Tailed Sample Distribution | 4 | eccv | 1 | 4 | 2023-06-17 00:59:20.327000 | https://github.com/yxymessi/h2e-framework | 71 | Identifying Hard Noise in Long-Tailed Sample Distribution | https://scholar.google.com/scholar?cluster=5820418443271560279&hl=en&as_sdt=0,5 | 5 | 2,022 |
NashAE: Disentangling Representations through Adversarial Covariance Minimization | 1 | eccv | 1 | 0 | 2023-06-17 00:59:20.539000 | https://github.com/ericyeats/nashae-beamsynthesis | 3 | NashAE: Disentangling Representations Through Adversarial Covariance Minimization | https://scholar.google.com/scholar?cluster=11326949042914417761&hl=en&as_sdt=0,33 | 1 | 2,022 |
Learning Visual Representation from Modality-Shared Contrastive Language-Image Pre-training | 16 | eccv | 2 | 0 | 2023-06-17 00:59:20.752000 | https://github.com/hxyou/msclip | 64 | Learning visual representation from modality-shared contrastive language-image pre-training | https://scholar.google.com/scholar?cluster=4379401598499228953&hl=en&as_sdt=0,5 | 4 | 2,022 |
Contrasting Quadratic Assignments for Set-Based Representation Learning | 3 | eccv | 0 | 0 | 2023-06-17 00:59:20.964000 | https://github.com/amoskalev/contrasting_quadratic | 8 | Contrasting quadratic assignments for set-based representation learning | https://scholar.google.com/scholar?cluster=6929984875841062884&hl=en&as_sdt=0,33 | 2 | 2,022 |
Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer | 7 | eccv | 0 | 4 | 2023-06-17 00:59:21.190000 | https://github.com/ashok-arjun/CSCCT | 13 | Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer | https://scholar.google.com/scholar?cluster=18267860036724176528&hl=en&as_sdt=0,39 | 1 | 2,022 |
MVDG: A Unified Multi-View Framework for Domain Generalization | 4 | eccv | 0 | 1 | 2023-06-17 00:59:21.403000 | https://github.com/koncle/mvdg | 4 | MVDG: A Unified Multi-view Framework for Domain Generalization | https://scholar.google.com/scholar?cluster=3734859660298356325&hl=en&as_sdt=0,5 | 1 | 2,022 |
Panoptic Scene Graph Generation | 17 | eccv | 53 | 13 | 2023-06-17 00:59:21.616000 | https://github.com/Jingkang50/OpenPSG | 305 | Panoptic scene graph generation | https://scholar.google.com/scholar?cluster=4427176906343613222&hl=en&as_sdt=0,5 | 6 | 2,022 |
Object-Compositional Neural Implicit Surfaces | 22 | eccv | 5 | 5 | 2023-06-17 00:59:21.829000 | https://github.com/qianyiwu/objsdf | 157 | Object-compositional neural implicit surfaces | https://scholar.google.com/scholar?cluster=9997708934654415598&hl=en&as_sdt=0,32 | 7 | 2,022 |
LiDAL: Inter-Frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentation | 6 | eccv | 2 | 0 | 2023-06-17 00:59:22.042000 | https://github.com/hzykent/lidal | 25 | LiDAL: Inter-frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentation | https://scholar.google.com/scholar?cluster=8461922341071305826&hl=en&as_sdt=0,5 | 3 | 2,022 |
DODA: Data-Oriented Sim-to-Real Domain Adaptation for 3D Semantic Segmentation | 2 | eccv | 4 | 5 | 2023-06-17 00:59:22.255000 | https://github.com/cvmi-lab/doda | 40 | DODA: Data-Oriented Sim-to-Real Domain Adaptation for 3D Semantic Segmentation | https://scholar.google.com/scholar?cluster=16242766710045978321&hl=en&as_sdt=0,37 | 4 | 2,022 |
TO-Scene: A Large-Scale Dataset for Understanding 3D Tabletop Scenes | 5 | eccv | 5 | 0 | 2023-06-17 00:59:22.466000 | https://github.com/GAP-LAB-CUHK-SZ/TO-Scene | 28 | TO-Scene: A Large-Scale Dataset for Understanding 3D Tabletop Scenes | https://scholar.google.com/scholar?cluster=18062236764908220812&hl=en&as_sdt=0,4 | 2 | 2,022 |
Fine-Grained Scene Graph Generation with Data Transfer | 14 | eccv | 6 | 4 | 2023-06-17 00:59:22.678000 | https://github.com/waxnkw/ietrans-sgg.pytorch | 69 | Fine-Grained Scene Graph Generation with Data Transfer | https://scholar.google.com/scholar?cluster=4124673263687372921&hl=en&as_sdt=0,25 | 1 | 2,022 |
Towards Hard-Positive Query Mining for DETR-Based Human-Object Interaction Detection | 4 | eccv | 1 | 0 | 2023-06-17 00:59:22.890000 | https://github.com/muchhair/hqm | 25 | Towards Hard-Positive Query Mining for DETR-Based Human-Object Interaction Detection | https://scholar.google.com/scholar?cluster=14859605205968905105&hl=en&as_sdt=0,5 | 1 | 2,022 |
PETR: Position Embedding Transformation for Multi-View 3D Object Detection | 118 | eccv | 87 | 43 | 2023-06-17 00:59:23.102000 | https://github.com/megvii-research/petr | 535 | Petr: Position embedding transformation for multi-view 3d object detection | https://scholar.google.com/scholar?cluster=3799744009906269739&hl=en&as_sdt=0,33 | 13 | 2,022 |
RA-Depth: Resolution Adaptive Self-Supervised Monocular Depth Estimation | 8 | eccv | 4 | 8 | 2023-06-17 00:59:23.315000 | https://github.com/hmhemu/ra-depth | 41 | RA-Depth: Resolution Adaptive Self-supervised Monocular Depth Estimation | https://scholar.google.com/scholar?cluster=10155818425251370358&hl=en&as_sdt=0,5 | 3 | 2,022 |
PolyphonicFormer: Unified Query Learning for Depth-Aware Video Panoptic Segmentation | 15 | eccv | 3 | 1 | 2023-06-17 00:59:23.527000 | https://github.com/harboryuan/polyphonicformer | 45 | Polyphonicformer: unified query learning for depth-aware video panoptic segmentation | https://scholar.google.com/scholar?cluster=7127843590064680446&hl=en&as_sdt=0,5 | 13 | 2,022 |
SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Clouds | 47 | eccv | 10 | 15 | 2023-06-17 00:59:23.739000 | https://github.com/QingyongHu/SQN | 83 | Sqn: Weakly-supervised semantic segmentation of large-scale 3d point clouds | https://scholar.google.com/scholar?cluster=4460489745797601457&hl=en&as_sdt=0,50 | 14 | 2,022 |
3D-PL: Domain Adaptive Depth Estimation with 3D-Aware Pseudo-Labeling | 1 | eccv | 1 | 3 | 2023-06-17 00:59:23.951000 | https://github.com/ccc870206/3d-pl | 15 | 3D-PL: Domain Adaptive Depth Estimation with 3D-Aware Pseudo-Labeling | https://scholar.google.com/scholar?cluster=15836829240967290716&hl=en&as_sdt=0,5 | 2 | 2,022 |
Panoptic-PartFormer: Learning a Unified Model for Panoptic Part Segmentation | 19 | eccv | 2 | 2 | 2023-06-17 00:59:24.162000 | https://github.com/lxtgh/panoptic-partformer | 46 | Panoptic-partformer: Learning a unified model for panoptic part segmentation | https://scholar.google.com/scholar?cluster=11513198882440237429&hl=en&as_sdt=0,5 | 4 | 2,022 |
Bi-PointFlowNet: Bidirectional Learning for Point Cloud Based Scene Flow Estimation | 12 | eccv | 4 | 1 | 2023-06-17 00:59:24.374000 | https://github.com/cwc1260/BiFlow | 12 | Bi-PointFlowNet: Bidirectional Learning for Point Cloud Based Scene Flow Estimation | https://scholar.google.com/scholar?cluster=12687214958834623027&hl=en&as_sdt=0,5 | 0 | 2,022 |
3DG-STFM: 3D Geometric Guided Student-Teacher Feature Matching | 0 | eccv | 2 | 0 | 2023-06-17 00:59:24.586000 | https://github.com/ryan-prime/3dg-stfm | 27 | 3DG-STFM: 3D Geometric Guided Student-Teacher Feature Matching | https://scholar.google.com/scholar?cluster=15958247080770709007&hl=en&as_sdt=0,47 | 2 | 2,022 |
MonteBoxFinder: Detecting and Filtering Primitives to Fit a Noisy Point Cloud | 1 | eccv | 0 | 0 | 2023-06-17 00:59:24.798000 | https://github.com/michaelramamonjisoa/monteboxfinder | 21 | MonteBoxFinder: Detecting and Filtering Primitives to Fit a Noisy Point Cloud | https://scholar.google.com/scholar?cluster=7470902724279064123&hl=en&as_sdt=0,6 | 1 | 2,022 |
Scene Text Recognition with Permuted Autoregressive Sequence Models | 23 | eccv | 85 | 26 | 2023-06-17 00:59:25.010000 | https://github.com/baudm/parseq | 338 | Scene text recognition with permuted autoregressive sequence models | https://scholar.google.com/scholar?cluster=8935992213517493527&hl=en&as_sdt=0,26 | 12 | 2,022 |
When Counting Meets HMER: Counting-Aware Network for Handwritten Mathematical Expression Recognition | 4 | eccv | 44 | 16 | 2023-06-17 00:59:25.221000 | https://github.com/lbh1024/can | 285 | When Counting Meets HMER: Counting-Aware Network for Handwritten Mathematical Expression Recognition | https://scholar.google.com/scholar?cluster=10414110543440415468&hl=en&as_sdt=0,15 | 23 | 2,022 |
GLASS: Global to Local Attention for Scene-Text Spotting | 7 | eccv | 7 | 9 | 2023-06-17 00:59:25.433000 | https://github.com/amazon-research/glass-text-spotting | 79 | Glass: Global to local attention for scene-text spotting | https://scholar.google.com/scholar?cluster=8076622804597824484&hl=en&as_sdt=0,22 | 4 | 2,022 |
COO: Comic Onomatopoeia Dataset for Recognizing Arbitrary or Truncated Texts | 3 | eccv | 1 | 0 | 2023-06-17 00:59:25.645000 | https://github.com/ku21fan/coo-comic-onomatopoeia | 38 | COO: Comic Onomatopoeia Dataset for Recognizing Arbitrary or Truncated Texts | https://scholar.google.com/scholar?cluster=1391865788632996555&hl=en&as_sdt=0,26 | 2 | 2,022 |
Toward Understanding WordArt: Corner-Guided Transformer for Scene Text Recognition | 4 | eccv | 11 | 3 | 2023-06-17 00:59:25.864000 | https://github.com/xdxie/wordart | 102 | Toward Understanding WordArt: Corner-Guided Transformer for Scene Text Recognition | https://scholar.google.com/scholar?cluster=6406452279700529821&hl=en&as_sdt=0,5 | 4 | 2,022 |
Dynamic Low-Resolution Distillation for Cost-Efficient End-to-End Text Spotting | 0 | eccv | 142 | 65 | 2023-06-17 00:59:26.076000 | https://github.com/hikopensource/davar-lab-ocr | 636 | Dynamic Low-Resolution Distillation for Cost-Efficient End-to-End Text Spotting | https://scholar.google.com/scholar?cluster=16011258404988613521&hl=en&as_sdt=0,50 | 25 | 2,022 |
CoMER: Modeling Coverage for Transformer-Based Handwritten Mathematical Expression Recognition | 3 | eccv | 13 | 8 | 2023-06-17 00:59:26.288000 | https://github.com/Green-Wood/CoMER | 61 | CoMER: Modeling Coverage for Transformer-Based Handwritten Mathematical Expression Recognition | https://scholar.google.com/scholar?cluster=5646141492436593798&hl=en&as_sdt=0,10 | 3 | 2,022 |
Don't Forget Me: Accurate Background Recovery for Text Removal via Modeling Local-Global Context | 2 | eccv | 5 | 10 | 2023-06-17 00:59:26.500000 | https://github.com/lcy0604/ctrnet | 50 | Don't Forget Me: Accurate Background Recovery for Text Removal via Modeling Local-Global Context | https://scholar.google.com/scholar?cluster=8104354788716938084&hl=en&as_sdt=0,33 | 1 | 2,022 |
TextAdaIN: Paying Attention to Shortcut Learning in Text Recognizers | 1 | eccv | 1 | 1 | 2023-06-17 00:59:26.712000 | https://github.com/amazon-research/textadain-robust-recognition | 19 | TextAdaIN: Paying Attention to Shortcut Learning in Text Recognizers | https://scholar.google.com/scholar?cluster=11280375643907122561&hl=en&as_sdt=0,31 | 3 | 2,022 |
Multi-modal Text Recognition Networks: Interactive Enhancements between Visual and Semantic Features | 13 | eccv | 6 | 0 | 2023-06-17 00:59:26.924000 | https://github.com/wp03052/MATRN | 56 | Multi-modal text recognition networks: Interactive enhancements between visual and semantic features | https://scholar.google.com/scholar?cluster=16909271202160367665&hl=en&as_sdt=0,10 | 3 | 2,022 |
CAR: Class-Aware Regularizations for Semantic Segmentation | 5 | eccv | 6 | 0 | 2023-06-17 00:59:27.136000 | https://github.com/edwardyehuang/CAR | 27 | Car: Class-aware regularizations for semantic segmentation | https://scholar.google.com/scholar?cluster=10799908460369282649&hl=en&as_sdt=0,47 | 3 | 2,022 |
Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentation | 10 | eccv | 3 | 1 | 2023-06-17 00:59:27.349000 | https://github.com/helioszhao/shade | 27 | Style-hallucinated dual consistency learning for domain generalized semantic segmentation | https://scholar.google.com/scholar?cluster=12065305653131607870&hl=en&as_sdt=0,47 | 2 | 2,022 |
In Defense of Online Models for Video Instance Segmentation | 35 | eccv | 49 | 38 | 2023-06-17 00:59:27.561000 | https://github.com/wjf5203/vnext | 547 | In defense of online models for video instance segmentation | https://scholar.google.com/scholar?cluster=16069829188377130053&hl=en&as_sdt=0,6 | 14 | 2,022 |
Active Pointly-Supervised Instance Segmentation | 2 | eccv | 0 | 0 | 2023-06-17 00:59:27.773000 | https://github.com/chufengt/APIS | 8 | Active Pointly-Supervised Instance Segmentation | https://scholar.google.com/scholar?cluster=10978471803996868329&hl=en&as_sdt=0,25 | 1 | 2,022 |
XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model | 48 | eccv | 118 | 2 | 2023-06-17 00:59:27.989000 | https://github.com/hkchengrex/XMem | 1,204 | XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model | https://scholar.google.com/scholar?cluster=4746998901966699571&hl=en&as_sdt=0,20 | 24 | 2,022 |
2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds | 42 | eccv | 40 | 24 | 2023-06-17 00:59:28.204000 | https://github.com/yanx27/2dpass | 306 | 2dpass: 2d priors assisted semantic segmentation on lidar point clouds | https://scholar.google.com/scholar?cluster=2558373953839539884&hl=en&as_sdt=0,6 | 15 | 2,022 |
Extract Free Dense Labels from CLIP | 52 | eccv | 21 | 8 | 2023-06-17 00:59:28.416000 | https://github.com/chongzhou96/maskclip | 244 | Extract free dense labels from clip | https://scholar.google.com/scholar?cluster=10784889589205919086&hl=en&as_sdt=0,44 | 7 | 2,022 |
Box-Supervised Instance Segmentation with Level Set Evolution | 14 | eccv | 24 | 6 | 2023-06-17 00:59:28.628000 | https://github.com/liwentomng/boxlevelset | 155 | Box-supervised instance segmentation with level set evolution | https://scholar.google.com/scholar?cluster=7955592219635477713&hl=en&as_sdt=0,1 | 5 | 2,022 |
Point Primitive Transformer for Long-Term 4D Point Cloud Video Understanding | 2 | eccv | 0 | 1 | 2023-06-17 00:59:28.840000 | https://github.com/hoi4d/PPTr | 6 | Point Primitive Transformer for Long-Term 4D Point Cloud Video Understanding | https://scholar.google.com/scholar?cluster=6712698866452693925&hl=en&as_sdt=0,31 | 1 | 2,022 |
TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation | 11 | eccv | 3 | 2 | 2023-06-17 00:59:29.053000 | https://github.com/damo-cv/transfgu | 26 | TransFGU: a top-down approach to fine-grained unsupervised semantic segmentation | https://scholar.google.com/scholar?cluster=8246429810533346263&hl=en&as_sdt=0,7 | 2 | 2,022 |
Cost Aggregation with 4D Convolutional Swin Transformer for Few-Shot Segmentation | 20 | eccv | 14 | 1 | 2023-06-17 00:59:29.268000 | https://github.com/Seokju-Cho/Volumetric-Aggregation-Transformer | 129 | Cost aggregation with 4d convolutional swin transformer for few-shot segmentation | https://scholar.google.com/scholar?cluster=7354076544100243051&hl=en&as_sdt=0,5 | 1 | 2,022 |
Perceptual Artifacts Localization for Inpainting | 3 | eccv | 0 | 1 | 2023-06-17 00:59:29.480000 | https://github.com/owenzlz/pal4inpaint | 28 | Perceptual artifacts localization for inpainting | https://scholar.google.com/scholar?cluster=15640327239633342238&hl=en&as_sdt=0,10 | 2 | 2,022 |
Data Efficient 3D Learner via Knowledge Transferred from 2D Model | 2 | eccv | 0 | 0 | 2023-06-17 00:59:29.700000 | https://github.com/bryanyu1997/data-efficient-3d-learner | 15 | Data Efficient 3D Learner via Knowledge Transferred from 2D Model | https://scholar.google.com/scholar?cluster=10623808226901890539&hl=en&as_sdt=0,5 | 2 | 2,022 |
Dense Gaussian Processes for Few-Shot Segmentation | 8 | eccv | 3 | 1 | 2023-06-17 00:59:29.911000 | https://github.com/joakimjohnander/dgpnet | 41 | Dense gaussian processes for few-shot segmentation | https://scholar.google.com/scholar?cluster=9696467800979236699&hl=en&as_sdt=0,34 | 2 | 2,022 |
3D Instances as 1D Kernels | 4 | eccv | 4 | 1 | 2023-06-17 00:59:30.124000 | https://github.com/w1zheng/dknet | 45 | 3D Instances as 1D Kernels | https://scholar.google.com/scholar?cluster=10539575323882110234&hl=en&as_sdt=0,6 | 3 | 2,022 |
TransMatting: Enhancing Transparent Objects Matting with Transformers | 6 | eccv | 2 | 1 | 2023-06-17 00:59:30.337000 | https://github.com/acechq/transmatting | 15 | TransMatting: Enhancing Transparent Objects Matting with Transformers | https://scholar.google.com/scholar?cluster=2970412112339223847&hl=en&as_sdt=0,47 | 8 | 2,022 |
Abstracting Sketches through Simple Primitives | 5 | eccv | 2 | 0 | 2023-06-17 00:59:30.549000 | https://github.com/explainableml/sketch-primitives | 15 | Abstracting sketches through simple primitives | https://scholar.google.com/scholar?cluster=12178522811290593447&hl=en&as_sdt=0,5 | 5 | 2,022 |
Multi-Scale and Cross-Scale Contrastive Learning for Semantic Segmentation | 1 | eccv | 2 | 1 | 2023-06-17 00:59:30.762000 | https://github.com/rvimlab/ms_cs_contrseg | 18 | Multi-scale and Cross-scale Contrastive Learning for Semantic Segmentation | https://scholar.google.com/scholar?cluster=2818282965941124519&hl=en&as_sdt=0,8 | 3 | 2,022 |
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