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One-Trimap Video Matting | 4 | eccv | 6 | 6 | 2023-06-17 00:59:30.985000 | https://github.com/hongje/otvm | 70 | One-Trimap Video Matting | https://scholar.google.com/scholar?cluster=7588838291826563440&hl=en&as_sdt=0,5 | 6 | 2,022 |
D2ADA: Dynamic Density-Aware Active Domain Adaptation for Semantic Segmentation | 1 | eccv | 0 | 2 | 2023-06-17 00:59:31.207000 | https://github.com/tsunghan-wu/d2ada | 19 | : Dynamic Density-Aware Active Domain Adaptation for Semantic Segmentation | https://scholar.google.com/scholar?cluster=13096093290067916309&hl=en&as_sdt=0,5 | 2 | 2,022 |
Learning Quality-Aware Dynamic Memory for Video Object Segmentation | 10 | eccv | 17 | 0 | 2023-06-17 00:59:31.451000 | https://github.com/workforai/qdmn | 131 | Learning quality-aware dynamic memory for video object segmentation | https://scholar.google.com/scholar?cluster=14581578558335348283&hl=en&as_sdt=0,5 | 6 | 2,022 |
Learning Implicit Feature Alignment Function for Semantic Segmentation | 14 | eccv | 1 | 5 | 2023-06-17 00:59:31.664000 | https://github.com/hzhupku/ifa | 58 | Learning implicit feature alignment function for semantic segmentation | https://scholar.google.com/scholar?cluster=16350586248496262508&hl=en&as_sdt=0,5 | 3 | 2,022 |
Instance As Identity: A Generic Online Paradigm for Video Instance Segmentation | 4 | eccv | 3 | 0 | 2023-06-17 00:59:31.876000 | https://github.com/zfonemore/iai | 16 | Instance as identity: A generic online paradigm for video instance segmentation | https://scholar.google.com/scholar?cluster=2651342369418937109&hl=en&as_sdt=0,44 | 1 | 2,022 |
Geodesic-Former: A Geodesic-Guided Few-Shot 3D Point Cloud Instance Segmenter | 2 | eccv | 2 | 1 | 2023-06-17 00:59:32.088000 | https://github.com/vinairesearch/geoformer | 14 | Geodesic-Former: A Geodesic-Guided Few-Shot 3D Point Cloud Instance Segmenter | https://scholar.google.com/scholar?cluster=5545556338836437482&hl=en&as_sdt=0,19 | 3 | 2,022 |
Union-Set Multi-source Model Adaptation for Semantic Segmentation | 2 | eccv | 1 | 0 | 2023-06-17 00:59:32.301000 | https://github.com/lzy7976/union-set-model-adaptation | 9 | Union-Set Multi-source Model Adaptation for Semantic Segmentation | https://scholar.google.com/scholar?cluster=8783974652276072046&hl=en&as_sdt=0,5 | 2 | 2,022 |
SPSN: Superpixel Prototype Sampling Network for RGB-D Salient Object Detection | 19 | eccv | 3 | 1 | 2023-06-17 00:59:32.513000 | https://github.com/Hydragon516/SPSN | 32 | Spsn: Superpixel prototype sampling network for rgb-d salient object detection | https://scholar.google.com/scholar?cluster=961197252690730583&hl=en&as_sdt=0,5 | 2 | 2,022 |
Global Spectral Filter Memory Network for Video Object Segmentation | 8 | eccv | 2 | 1 | 2023-06-17 00:59:32.727000 | https://github.com/workforai/gsfm | 29 | Global spectral filter memory network for video object segmentation | https://scholar.google.com/scholar?cluster=6531040020135946124&hl=en&as_sdt=0,47 | 3 | 2,022 |
Video Instance Segmentation via Multi-Scale Spatio-Temporal Split Attention Transformer | 6 | eccv | 2 | 3 | 2023-06-17 00:59:32.946000 | https://github.com/OmkarThawakar/MSSTS-VIS | 36 | Video Instance Segmentation via Multi-Scale Spatio-Temporal Split Attention Transformer | https://scholar.google.com/scholar?cluster=971651369893003442&hl=en&as_sdt=0,23 | 8 | 2,022 |
Learning Topological Interactions for Multi-Class Medical Image Segmentation | 5 | eccv | 5 | 0 | 2023-06-17 00:59:33.162000 | https://github.com/topoxlab/topointeraction | 53 | Learning Topological Interactions for Multi-Class Medical Image Segmentation | https://scholar.google.com/scholar?cluster=7636749497701353644&hl=en&as_sdt=0,30 | 4 | 2,022 |
Unsupervised Segmentation in Real-World Images via Spelke Object Inference | 8 | eccv | 2 | 4 | 2023-06-17 00:59:33.382000 | https://github.com/neuroailab/eisen | 20 | Unsupervised segmentation in real-world images via spelke object inference | https://scholar.google.com/scholar?cluster=17744200822268427620&hl=en&as_sdt=0,5 | 4 | 2,022 |
A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-Language Model | 23 | eccv | 10 | 6 | 2023-06-17 00:59:33.594000 | https://github.com/mendelxu/zsseg.baseline | 126 | A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-Language Model | https://scholar.google.com/scholar?cluster=1990243593035555434&hl=en&as_sdt=0,5 | 5 | 2,022 |
Generative Subgraph Contrast for Self-Supervised Graph Representation Learning | 1 | eccv | 1 | 0 | 2023-06-17 00:59:33.808000 | https://github.com/yh-han/gsc | 11 | Generative Subgraph Contrast for Self-Supervised Graph Representation Learning | https://scholar.google.com/scholar?cluster=17324044096784760749&hl=en&as_sdt=0,26 | 1 | 2,022 |
SdAE: Self-Distillated Masked Autoencoder | 18 | eccv | 1 | 2 | 2023-06-17 00:59:34.020000 | https://github.com/abrahamyabo/sdae | 36 | Sdae: Self-distillated masked autoencoder | https://scholar.google.com/scholar?cluster=6427547624181496716&hl=en&as_sdt=0,5 | 4 | 2,022 |
Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation | 7 | eccv | 2 | 0 | 2023-06-17 00:59:34.232000 | https://github.com/val-iisc/stickerda | 17 | Concurrent subsidiary supervision for unsupervised source-free domain adaptation | https://scholar.google.com/scholar?cluster=16781913863489916282&hl=en&as_sdt=0,5 | 12 | 2,022 |
Active Learning Strategies for Weakly-Supervised Object Detection | 3 | eccv | 5 | 1 | 2023-06-17 00:59:34.445000 | https://github.com/huyvvo/bib | 25 | Active Learning Strategies for Weakly-Supervised Object Detection | https://scholar.google.com/scholar?cluster=6555341052977464243&hl=en&as_sdt=0,5 | 2 | 2,022 |
Mc-BEiT: Multi-Choice Discretization for Image BERT Pre-training | 18 | eccv | 1 | 0 | 2023-06-17 00:59:34.656000 | https://github.com/lixiaotong97/mc-beit | 21 | mc-BEiT: Multi-choice Discretization for Image BERT Pre-training | https://scholar.google.com/scholar?cluster=10612926957976727479&hl=en&as_sdt=0,5 | 2 | 2,022 |
Bootstrapped Masked Autoencoders for Vision BERT Pretraining | 18 | eccv | 6 | 0 | 2023-06-17 00:59:34.868000 | https://github.com/lightdxy/bootmae | 90 | Bootstrapped Masked Autoencoders for Vision BERT Pretraining | https://scholar.google.com/scholar?cluster=11908913569029309505&hl=en&as_sdt=0,10 | 3 | 2,022 |
What to Hide from Your Students: Attention-Guided Masked Image Modeling | 36 | eccv | 4 | 0 | 2023-06-17 00:59:35.089000 | https://github.com/gkakogeorgiou/attmask | 31 | What to hide from your students: Attention-guided masked image modeling | https://scholar.google.com/scholar?cluster=13621702207944750833&hl=en&as_sdt=0,5 | 5 | 2,022 |
Pointly-Supervised Panoptic Segmentation | 5 | eccv | 1 | 1 | 2023-06-17 00:59:35.307000 | https://github.com/bravegroup/psps | 19 | Pointly-Supervised Panoptic Segmentation | https://scholar.google.com/scholar?cluster=14167808655489374713&hl=en&as_sdt=0,1 | 4 | 2,022 |
HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation | 43 | eccv | 25 | 4 | 2023-06-17 00:59:35.524000 | https://github.com/lhoyer/hrda | 188 | HRDA: Context-aware high-resolution domain-adaptive semantic segmentation | https://scholar.google.com/scholar?cluster=11500016484284904863&hl=en&as_sdt=0,5 | 5 | 2,022 |
Unsupervised Selective Labeling for More Effective Semi-Supervised Learning | 6 | eccv | 3 | 1 | 2023-06-17 00:59:35.760000 | https://github.com/TonyLianLong/UnsupervisedSelectiveLabeling | 27 | Unsupervised Selective Labeling for More Effective Semi-Supervised Learning | https://scholar.google.com/scholar?cluster=2772643387348706767&hl=en&as_sdt=0,28 | 2 | 2,022 |
Max Pooling with Vision Transformers Reconciles Class and Shape in Weakly Supervised Semantic Segmentation | 10 | eccv | 1 | 0 | 2023-06-17 00:59:36.028000 | https://github.com/deepplants/vit-pcm | 14 | Max Pooling with Vision Transformers reconciles class and shape in weakly supervised semantic segmentation | https://scholar.google.com/scholar?cluster=13877065122591623844&hl=en&as_sdt=0,5 | 2 | 2,022 |
Dense Siamese Network for Dense Unsupervised Learning | 4 | eccv | 2 | 0 | 2023-06-17 00:59:36.298000 | https://github.com/zwwwayne/densesiam | 26 | Dense Siamese Network for Dense Unsupervised Learning | https://scholar.google.com/scholar?cluster=2962540697381771652&hl=en&as_sdt=0,25 | 1 | 2,022 |
Multi-Granularity Distillation Scheme towards Lightweight Semi-Supervised Semantic Segmentation | 2 | eccv | 1 | 3 | 2023-06-17 00:59:36.510000 | https://github.com/jayqine/mgd-ssss | 11 | Multi-granularity Distillation Scheme Towards Lightweight Semi-supervised Semantic Segmentation | https://scholar.google.com/scholar?cluster=14826363507378603600&hl=en&as_sdt=0,47 | 3 | 2,022 |
CP2: Copy-Paste Contrastive Pretraining for Semantic Segmentation | 10 | eccv | 1 | 0 | 2023-06-17 00:59:36.723000 | https://github.com/wangf3014/cp2 | 6 | CP: Copy-Paste Contrastive Pretraining for Semantic Segmentation | https://scholar.google.com/scholar?cluster=9077524711445116563&hl=en&as_sdt=0,5 | 1 | 2,022 |
Self-Filtering: A Noise-Aware Sample Selection for Label Noise with Confidence Penalization | 7 | eccv | 2 | 0 | 2023-06-17 00:59:36.934000 | https://github.com/1998v7/self-filtering | 19 | Self-Filtering: A Noise-Aware Sample Selection for Label Noise with Confidence Penalization | https://scholar.google.com/scholar?cluster=11503343963876701921&hl=en&as_sdt=0,36 | 1 | 2,022 |
RDA: Reciprocal Distribution Alignment for Robust Semi-Supervised Learning | 1 | eccv | 0 | 0 | 2023-06-17 00:59:37.155000 | https://github.com/njuyued/rda4robustssl | 7 | RDA: Reciprocal Distribution Alignment for Robust Semi-supervised Learning | https://scholar.google.com/scholar?cluster=1893818676204532459&hl=en&as_sdt=0,11 | 1 | 2,022 |
MemSAC: Memory Augmented Sample Consistency for Large Scale Domain Adaptation | 1 | eccv | 0 | 0 | 2023-06-17 00:59:37.368000 | https://github.com/ViLab-UCSD/MemSAC_ECCV2022 | 6 | MemSAC: Memory Augmented Sample Consistency for Large Scale Domain Adaptation | https://scholar.google.com/scholar?cluster=17292964986746280650&hl=en&as_sdt=0,5 | 2 | 2,022 |
Synergistic Self-Supervised and Quantization Learning | 2 | eccv | 4 | 0 | 2023-06-17 00:59:37.583000 | https://github.com/megvii-research/ssql-eccv2022 | 67 | Synergistic Self-supervised and Quantization Learning | https://scholar.google.com/scholar?cluster=3701150918575417216&hl=en&as_sdt=0,23 | 4 | 2,022 |
Semi-Supervised Vision Transformers | 14 | eccv | 5 | 1 | 2023-06-17 00:59:37.798000 | https://github.com/wengzejia1/semiformer | 26 | Semi-supervised vision transformers | https://scholar.google.com/scholar?cluster=83081748366699225&hl=en&as_sdt=0,5 | 3 | 2,022 |
Domain Adaptive Video Segmentation via Temporal Pseudo Supervision | 5 | eccv | 6 | 9 | 2023-06-17 00:59:38.011000 | https://github.com/xing0047/tps | 28 | Domain adaptive video segmentation via temporal pseudo supervision | https://scholar.google.com/scholar?cluster=7231098623956259110&hl=en&as_sdt=0,5 | 2 | 2,022 |
ConMatch: Semi-Supervised Learning with Confidence-Guided Consistency Regularization | 6 | eccv | 3 | 1 | 2023-06-17 00:59:38.224000 | https://github.com/jiwoncocoder/conmatch | 24 | Conmatch: Semi-supervised learning with confidence-guided consistency regularization | https://scholar.google.com/scholar?cluster=23511256883904024&hl=en&as_sdt=0,10 | 4 | 2,022 |
FedX: Unsupervised Federated Learning with Cross Knowledge Distillation | 6 | eccv | 6 | 0 | 2023-06-17 00:59:38.436000 | https://github.com/sungwon-han/fedx | 47 | FedX: Unsupervised Federated Learning with Cross Knowledge Distillation | https://scholar.google.com/scholar?cluster=15024670483115601107&hl=en&as_sdt=0,44 | 3 | 2,022 |
Decoupled Adversarial Contrastive Learning for Self-Supervised Adversarial Robustness | 6 | eccv | 1 | 1 | 2023-06-17 00:59:38.649000 | https://github.com/pantheon5100/deacl | 12 | Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness | https://scholar.google.com/scholar?cluster=33793130511872188&hl=en&as_sdt=0,23 | 3 | 2,022 |
GOCA: Guided Online Cluster Assignment for Self-Supervised Video Representation Learning | 2 | eccv | 1 | 1 | 2023-06-17 00:59:38.861000 | https://github.com/seleucia/goca | 7 | GOCA: guided online cluster assignment for self-supervised video representation Learning | https://scholar.google.com/scholar?cluster=11832380063761473468&hl=en&as_sdt=0,47 | 1 | 2,022 |
Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning | 1 | eccv | 2 | 0 | 2023-06-17 00:59:39.074000 | https://github.com/ucdvision/cmsf | 5 | Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning | https://scholar.google.com/scholar?cluster=3423733438227857877&hl=en&as_sdt=0,5 | 3 | 2,022 |
Revisiting the Critical Factors of Augmentation-Invariant Representation Learning | 3 | eccv | 0 | 0 | 2023-06-17 00:59:39.287000 | https://github.com/megvii-research/revisitairl | 11 | Revisiting the Critical Factors of Augmentation-Invariant Representation Learning | https://scholar.google.com/scholar?cluster=5620391103702962878&hl=en&as_sdt=0,33 | 3 | 2,022 |
CA-SSL: Class-Agnostic Semi-Supervised Learning for Detection and Segmentation | 2 | eccv | 42 | 19 | 2023-06-17 00:59:39.498000 | https://github.com/dvlab-research/Entity | 449 | CA-SSL: Class-Agnostic Semi-Supervised Learning for Detection and Segmentation | https://scholar.google.com/scholar?cluster=9702778436571703527&hl=en&as_sdt=0,31 | 20 | 2,022 |
Semantic-Aware Fine-Grained Correspondence | 2 | eccv | 1 | 1 | 2023-06-17 00:59:39.710000 | https://github.com/alxead/sfc | 13 | Semantic-Aware Fine-Grained Correspondence | https://scholar.google.com/scholar?cluster=9515469045960583745&hl=en&as_sdt=0,14 | 1 | 2,022 |
Self-Supervised Classification Network | 15 | eccv | 4 | 0 | 2023-06-17 00:59:39.924000 | https://github.com/elad-amrani/self-classifier | 31 | Self-supervised classification network | https://scholar.google.com/scholar?cluster=12911109870349597402&hl=en&as_sdt=0,31 | 1 | 2,022 |
Semi-Supervised Object Detection via Virtual Category Learning | 5 | eccv | 0 | 0 | 2023-06-17 00:59:40.135000 | https://github.com/geoffreychen777/vc | 6 | Semi-supervised object detection via virtual category learning | https://scholar.google.com/scholar?cluster=12705891433611100689&hl=en&as_sdt=0,10 | 1 | 2,022 |
Completely Self-Supervised Crowd Counting via Distribution Matching | 7 | eccv | 8 | 1 | 2023-06-17 00:59:40.348000 | https://github.com/val-iisc/css-ccnn | 25 | Completely self-supervised crowd counting via distribution matching | https://scholar.google.com/scholar?cluster=15996947716561762009&hl=en&as_sdt=0,5 | 14 | 2,022 |
Coarse-to-Fine Incremental Few-Shot Learning | 4 | eccv | 0 | 0 | 2023-06-17 00:59:40.561000 | https://github.com/HAIV-Lab/Knowe | 4 | Coarse-to-fine incremental few-shot learning | https://scholar.google.com/scholar?cluster=15208517894348282835&hl=en&as_sdt=0,5 | 0 | 2,022 |
Learning Unbiased Transferability for Domain Adaptation by Uncertainty Modeling | 0 | eccv | 1 | 0 | 2023-06-17 00:59:40.774000 | https://github.com/puchapu/utep | 2 | Learning Unbiased Transferability for Domain Adaptation by Uncertainty Modeling | https://scholar.google.com/scholar?cluster=10772316129311859971&hl=en&as_sdt=0,5 | 1 | 2,022 |
CYBORGS: Contrastively Bootstrapping Object Representations by Grounding in Segmentation | 2 | eccv | 0 | 1 | 2023-06-17 00:59:40.986000 | https://github.com/renwang435/cyborgs | 3 | Cyborgs: Contrastively bootstrapping object representations by grounding in segmentation | https://scholar.google.com/scholar?cluster=4093202168544509121&hl=en&as_sdt=0,5 | 2 | 2,022 |
Object Discovery via Contrastive Learning for Weakly Supervised Object Detection | 4 | eccv | 4 | 4 | 2023-06-17 00:59:41.207000 | https://github.com/jinhseo/od-wscl | 31 | Object Discovery via Contrastive Learning for Weakly Supervised Object Detection | https://scholar.google.com/scholar?cluster=4274032166116217116&hl=en&as_sdt=0,5 | 1 | 2,022 |
Semi-Leak: Membership Inference Attacks against Semi-Supervised Learning | 3 | eccv | 0 | 0 | 2023-06-17 00:59:41.420000 | https://github.com/xinleihe/semi-leak | 9 | Semi-Leak: Membership Inference Attacks Against Semi-supervised Learning | https://scholar.google.com/scholar?cluster=9233507844643867685&hl=en&as_sdt=0,5 | 1 | 2,022 |
OpenLDN: Learning to Discover Novel Classes for Open-World Semi-Supervised Learning | 7 | eccv | 4 | 3 | 2023-06-17 00:59:41.632000 | https://github.com/nayeemrizve/openldn | 23 | Openldn: Learning to discover novel classes for open-world semi-supervised learning | https://scholar.google.com/scholar?cluster=12710236080905969514&hl=en&as_sdt=0,5 | 1 | 2,022 |
Embedding Contrastive Unsupervised Features to Cluster in- and Out-of-Distribution Noise in Corrupted Image Datasets | 2 | eccv | 0 | 1 | 2023-06-17 00:59:41.845000 | https://github.com/paulalbert31/sncf | 9 | Embedding contrastive unsupervised features to cluster in-and out-of-distribution noise in corrupted image datasets | https://scholar.google.com/scholar?cluster=6052251975448117268&hl=en&as_sdt=0,26 | 2 | 2,022 |
Towards Realistic Semi-Supervised Learning | 8 | eccv | 1 | 3 | 2023-06-17 00:59:42.058000 | https://github.com/nayeemrizve/trssl | 24 | Towards realistic semi-supervised learning | https://scholar.google.com/scholar?cluster=15906626340629740128&hl=en&as_sdt=0,5 | 1 | 2,022 |
Masked Siamese Networks for Label-Efficient Learning | 99 | eccv | 30 | 16 | 2023-06-17 00:59:42.271000 | https://github.com/facebookresearch/msn | 400 | Masked siamese networks for label-efficient learning | https://scholar.google.com/scholar?cluster=9235835052951341282&hl=en&as_sdt=0,23 | 13 | 2,022 |
Natural Synthetic Anomalies for Self-Supervised Anomaly Detection and Localization | 17 | eccv | 5 | 1 | 2023-06-17 00:59:42.483000 | https://github.com/hmsch/natural-synthetic-anomalies | 29 | Natural synthetic anomalies for self-supervised anomaly detection and localization | https://scholar.google.com/scholar?cluster=7248162955817269145&hl=en&as_sdt=0,5 | 2 | 2,022 |
Understanding Collapse in Non-Contrastive Siamese Representation Learning | 10 | eccv | 1 | 1 | 2023-06-17 00:59:42.695000 | https://github.com/alexlioralexli/noncontrastive-ssl | 4 | Understanding Collapse in Non-contrastive Siamese Representation Learning | https://scholar.google.com/scholar?cluster=1641172093663463753&hl=en&as_sdt=0,44 | 1 | 2,022 |
Federated Self-Supervised Learning for Video Understanding | 2 | eccv | 1 | 0 | 2023-06-17 00:59:42.908000 | https://github.com/yasar-rehman/fedvssl | 15 | Federated Self-supervised Learning for Video Understanding | https://scholar.google.com/scholar?cluster=5203922739716905699&hl=en&as_sdt=0,4 | 6 | 2,022 |
Towards Efficient and Effective Self-Supervised Learning of Visual Representations | 3 | eccv | 1 | 0 | 2023-06-17 00:59:43.120000 | https://github.com/val-iisc/effssl | 4 | Towards Efficient and Effective Self-Supervised Learning of Visual Representations | https://scholar.google.com/scholar?cluster=9102827506777394507&hl=en&as_sdt=0,44 | 13 | 2,022 |
MVSTER: Epipolar Transformer for Efficient Multi-View Stereo | 20 | eccv | 12 | 10 | 2023-06-17 00:59:43.333000 | https://github.com/jeffwang987/mvster | 149 | MVSTER: epipolar transformer for efficient multi-view stereo | https://scholar.google.com/scholar?cluster=16748508301109808969&hl=en&as_sdt=0,5 | 6 | 2,022 |
RC-MVSNet: Unsupervised Multi-View Stereo with Neural Rendering | 10 | eccv | 13 | 7 | 2023-06-17 00:59:43.545000 | https://github.com/boese0601/rc-mvsnet | 173 | RC-MVSNet: unsupervised multi-view stereo with neural rendering | https://scholar.google.com/scholar?cluster=7214458458085402585&hl=en&as_sdt=0,22 | 17 | 2,022 |
ARF: Artistic Radiance Fields | 30 | eccv | 41 | 7 | 2023-06-17 00:59:43.758000 | https://github.com/Kai-46/ARF-svox2 | 435 | Arf: Artistic radiance fields | https://scholar.google.com/scholar?cluster=9612416165197735153&hl=en&as_sdt=0,16 | 18 | 2,022 |
Multiview Stereo with Cascaded Epipolar RAFT | 5 | eccv | 9 | 4 | 2023-06-17 00:59:43.970000 | https://github.com/princeton-vl/cer-mvs | 100 | Multiview stereo with cascaded epipolar raft | https://scholar.google.com/scholar?cluster=5026889917906841246&hl=en&as_sdt=0,43 | 9 | 2,022 |
ASpanFormer: Detector-Free Image Matching with Adaptive Span Transformer | 27 | eccv | 16 | 0 | 2023-06-17 00:59:44.241000 | https://github.com/apple/ml-aspanformer | 100 | Aspanformer: Detector-free image matching with adaptive span transformer | https://scholar.google.com/scholar?cluster=4389376922954725361&hl=en&as_sdt=0,37 | 12 | 2,022 |
NDF: Neural Deformable Fields for Dynamic Human Modelling | 4 | eccv | 4 | 1 | 2023-06-17 00:59:44.453000 | https://github.com/hkbu-vscomputing/2022_eccv_ndf | 14 | NDF: Neural Deformable Fields for Dynamic Human Modelling | https://scholar.google.com/scholar?cluster=10897766450583864581&hl=en&as_sdt=0,5 | 1 | 2,022 |
Neural Density-Distance Fields | 5 | eccv | 8 | 3 | 2023-06-17 00:59:44.665000 | https://github.com/ueda0319/neddf | 203 | Neural Density-Distance Fields | https://scholar.google.com/scholar?cluster=10169858113129806585&hl=en&as_sdt=0,5 | 13 | 2,022 |
Learning Online Multi-sensor Depth Fusion | 1 | eccv | 0 | 0 | 2023-06-17 00:59:44.878000 | https://github.com/tfy14esa/senfunet | 7 | Learning online multi-sensor depth fusion | https://scholar.google.com/scholar?cluster=12133624018619212262&hl=en&as_sdt=0,43 | 2 | 2,022 |
Improving RGB-D Point Cloud Registration by Learning Multi-Scale Local Linear Transformation | 1 | eccv | 0 | 0 | 2023-06-17 00:59:45.090000 | https://github.com/514dna/llt | 11 | Improving rgb-d point cloud registration by learning multi-scale local linear transformation | https://scholar.google.com/scholar?cluster=467163058867525578&hl=en&as_sdt=0,5 | 3 | 2,022 |
Real-Time Neural Character Rendering with Pose-Guided Multiplane Images | 6 | eccv | 5 | 1 | 2023-06-17 00:59:45.303000 | https://github.com/ken-ouyang/PGMPI | 46 | Real-time neural character rendering with pose-guided multiplane images | https://scholar.google.com/scholar?cluster=9080153091759921402&hl=en&as_sdt=0,5 | 3 | 2,022 |
Disentangling Object Motion and Occlusion for Unsupervised Multi-Frame Monocular Depth | 7 | eccv | 8 | 5 | 2023-06-17 00:59:45.514000 | https://github.com/AutoAILab/DynamicDepth | 96 | Disentangling Object Motion and Occlusion for Unsupervised Multi-frame Monocular Depth | https://scholar.google.com/scholar?cluster=7095473850872719452&hl=en&as_sdt=0,5 | 3 | 2,022 |
Context-Enhanced Stereo Transformer | 2 | eccv | 3 | 3 | 2023-06-17 00:59:45.727000 | https://github.com/guoweiyu/context-enhanced-stereo-transformer | 30 | Context-Enhanced Stereo Transformer | https://scholar.google.com/scholar?cluster=3543640163219156828&hl=en&as_sdt=0,25 | 1 | 2,022 |
Gen6D: Generalizable Model-Free 6-DoF Object Pose Estimation from RGB Images | 9 | eccv | 50 | 56 | 2023-06-17 00:59:45.940000 | https://github.com/liuyuan-pal/gen6d | 395 | Gen6D: Generalizable model-free 6-DoF object pose estimation from RGB images | https://scholar.google.com/scholar?cluster=5099493959917547229&hl=en&as_sdt=0,42 | 9 | 2,022 |
Latency-Aware Collaborative Perception | 20 | eccv | 1 | 2 | 2023-06-17 00:59:46.152000 | https://github.com/mediabrain-sjtu/syncnet | 13 | Latency-aware collaborative perception | https://scholar.google.com/scholar?cluster=12080385681051469958&hl=en&as_sdt=0,5 | 0 | 2,022 |
TensoRF: Tensorial Radiance Fields | 230 | eccv | 126 | 45 | 2023-06-17 00:59:46.364000 | https://github.com/apchenstu/TensoRF | 898 | Tensorf: Tensorial radiance fields | https://scholar.google.com/scholar?cluster=9392347583762409161&hl=en&as_sdt=0,29 | 20 | 2,022 |
NeFSAC: Neurally Filtered Minimal Samples | 5 | eccv | 1 | 1 | 2023-06-17 00:59:46.576000 | https://github.com/cavalli1234/nefsac | 36 | NeFSAC: neurally filtered minimal samples | https://scholar.google.com/scholar?cluster=13860320733798826375&hl=en&as_sdt=0,5 | 6 | 2,022 |
HDR-Plenoxels: Self-Calibrating High Dynamic Range Radiance Fields | 4 | eccv | 7 | 3 | 2023-06-17 00:59:46.788000 | https://github.com/postech-ami/hdr-plenoxels | 90 | HDR-Plenoxels: Self-Calibrating High Dynamic Range Radiance Fields | https://scholar.google.com/scholar?cluster=13393942085458083922&hl=en&as_sdt=0,39 | 9 | 2,022 |
NeuMan: Neural Human Radiance Field from a Single Video | 43 | eccv | 135 | 38 | 2023-06-17 00:59:47 | https://github.com/apple/ml-neuman | 1,096 | Neuman: Neural human radiance field from a single video | https://scholar.google.com/scholar?cluster=4308511704577688456&hl=en&as_sdt=0,5 | 35 | 2,022 |
TAVA: Template-Free Animatable Volumetric Actors | 33 | eccv | 16 | 1 | 2023-06-17 00:59:47.217000 | https://github.com/facebookresearch/tava | 179 | Tava: Template-free animatable volumetric actors | https://scholar.google.com/scholar?cluster=7969304324450759992&hl=en&as_sdt=0,29 | 12 | 2,022 |
EASNet: Searching Elastic and Accurate Network Architecture for Stereo Matching | 2 | eccv | 0 | 0 | 2023-06-17 00:59:47.430000 | https://github.com/hkbu-hpml/easnet | 6 | EASNet: Searching Elastic and Accurate Network Architecture for Stereo Matching | https://scholar.google.com/scholar?cluster=15435889328607570391&hl=en&as_sdt=0,5 | 1 | 2,022 |
ParticleSfM: Exploiting Dense Point Trajectories for Localizing Moving Cameras in the Wild | 5 | eccv | 15 | 3 | 2023-06-17 00:59:47.642000 | https://github.com/bytedance/particle-sfm | 160 | ParticleSfM: Exploiting Dense Point Trajectories for Localizing Moving Cameras in the Wild | https://scholar.google.com/scholar?cluster=649075297016253795&hl=en&as_sdt=0,5 | 14 | 2,022 |
Approximate Differentiable Rendering with Algebraic Surfaces | 2 | eccv | 2 | 2 | 2023-06-17 00:59:47.855000 | https://github.com/leonidk/fuzzy-metaballs | 48 | Approximate Differentiable Rendering with Algebraic Surfaces | https://scholar.google.com/scholar?cluster=14972940426953053796&hl=en&as_sdt=0,5 | 3 | 2,022 |
GraphFit: Learning Multi-Scale Graph-Convolutional Representation for Point Cloud Normal Estimation | 4 | eccv | 2 | 0 | 2023-06-17 00:59:48.069000 | https://github.com/uestcjay/graphfit | 21 | GraphFit: Learning Multi-scale Graph-Convolutional Representation for Point Cloud Normal Estimation | https://scholar.google.com/scholar?cluster=13505484244080411576&hl=en&as_sdt=0,38 | 1 | 2,022 |
Point Scene Understanding via Disentangled Instance Mesh Reconstruction | 6 | eccv | 3 | 4 | 2023-06-17 00:59:48.281000 | https://github.com/ashawkey/dimr | 25 | Point scene understanding via disentangled instance mesh reconstruction | https://scholar.google.com/scholar?cluster=2693964574751110058&hl=en&as_sdt=0,5 | 5 | 2,022 |
Space-Partitioning RANSAC | 3 | eccv | 79 | 7 | 2023-06-17 00:59:48.493000 | https://github.com/danini/graph-cut-ransac | 335 | Space-Partitioning RANSAC | https://scholar.google.com/scholar?cluster=7758768906343068839&hl=en&as_sdt=0,33 | 21 | 2,022 |
What Matters for 3D Scene Flow Network | 10 | eccv | 4 | 3 | 2023-06-17 00:59:48.705000 | https://github.com/irmvlab/3dflow | 36 | What Matters for 3D Scene Flow Network | https://scholar.google.com/scholar?cluster=15648120699613324906&hl=en&as_sdt=0,31 | 2 | 2,022 |
GraphCSPN: Geometry-Aware Depth Completion via Dynamic GCNs | 3 | eccv | 1 | 3 | 2023-06-17 00:59:48.918000 | https://github.com/xinliu20/graphcspn_eccv2022 | 15 | GraphCSPN: Geometry-Aware Depth Completion via Dynamic GCNs | https://scholar.google.com/scholar?cluster=1840962488966960353&hl=en&as_sdt=0,43 | 2 | 2,022 |
Language-Grounded Indoor 3D Semantic Segmentation in the Wild | 5 | eccv | 14 | 1 | 2023-06-17 00:59:49.130000 | https://github.com/RozDavid/LanguageGroundedSemseg | 77 | Language-grounded indoor 3D semantic segmentation in the wild | https://scholar.google.com/scholar?cluster=4523012745679704845&hl=en&as_sdt=0,47 | 4 | 2,022 |
FLEX: Extrinsic Parameters-Free Multi-View 3D Human Motion Reconstruction | 7 | eccv | 4 | 10 | 2023-06-17 00:59:49.342000 | https://github.com/BrianG13/FLEX | 37 | FLEX: Extrinsic Parameters-free Multi-view 3D Human Motion Reconstruction | https://scholar.google.com/scholar?cluster=9329272626865528352&hl=en&as_sdt=0,47 | 8 | 2,022 |
ActiveNeRF: Learning Where to See with Uncertainty Estimation | 7 | eccv | 3 | 4 | 2023-06-17 00:59:49.554000 | https://github.com/leaplabthu/activenerf | 58 | ActiveNeRF: Learning Where to See with Uncertainty Estimation | https://scholar.google.com/scholar?cluster=7696752785009743824&hl=en&as_sdt=0,5 | 6 | 2,022 |
PoserNet: Refining Relative Camera Poses Exploiting Object Detections | 1 | eccv | 0 | 0 | 2023-06-17 00:59:49.766000 | https://github.com/iit-pavis/posernet | 40 | PoserNet: Refining Relative Camera Poses Exploiting Object Detections | https://scholar.google.com/scholar?cluster=5415819577360667082&hl=en&as_sdt=0,39 | 6 | 2,022 |
Class-Incremental Novel Class Discovery | 9 | eccv | 6 | 2 | 2023-06-17 00:59:49.980000 | https://github.com/oatmealliu/class-incd | 55 | Class-incremental Novel Class Discovery | https://scholar.google.com/scholar?cluster=16320430811292329479&hl=en&as_sdt=0,5 | 4 | 2,022 |
Prototype-Guided Continual Adaptation for Class-Incremental Unsupervised Domain Adaptation | 7 | eccv | 1 | 1 | 2023-06-17 00:59:50.223000 | https://github.com/hongbin98/proca | 20 | Prototype-guided continual adaptation for class-incremental unsupervised domain adaptation | https://scholar.google.com/scholar?cluster=8804941606286373494&hl=en&as_sdt=0,39 | 3 | 2,022 |
DecoupleNet: Decoupled Network for Domain Adaptive Semantic Segmentation | 17 | eccv | 2 | 0 | 2023-06-17 00:59:50.436000 | https://github.com/dvlab-research/decouplenet | 30 | DecoupleNet: Decoupled network for domain adaptive semantic segmentation | https://scholar.google.com/scholar?cluster=9009915321489245170&hl=en&as_sdt=0,5 | 3 | 2,022 |
Mind the Gap in Distilling StyleGANs | 4 | eccv | 1 | 3 | 2023-06-17 00:59:50.647000 | https://github.com/xuguodong03/stylekd | 22 | Mind the Gap in Distilling StyleGANs | https://scholar.google.com/scholar?cluster=5377121854905583705&hl=en&as_sdt=0,47 | 7 | 2,022 |
Long-Tailed Class Incremental Learning | 2 | eccv | 0 | 0 | 2023-06-17 00:59:50.859000 | https://github.com/xialeiliu/long-tailed-cil | 26 | Long-Tailed Class Incremental Learning | https://scholar.google.com/scholar?cluster=9618483384480829027&hl=en&as_sdt=0,14 | 6 | 2,022 |
GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation | 5 | eccv | 1 | 0 | 2023-06-17 00:59:51.071000 | https://github.com/saltoricristiano/gipso-sfouda | 31 | GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation | https://scholar.google.com/scholar?cluster=13813760731976228346&hl=en&as_sdt=0,33 | 6 | 2,022 |
CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentation | 17 | eccv | 5 | 0 | 2023-06-17 00:59:51.284000 | https://github.com/saltoricristiano/cosmix-uda | 40 | Cosmix: Compositional semantic mix for domain adaptation in 3d lidar segmentation | https://scholar.google.com/scholar?cluster=6786759772054921592&hl=en&as_sdt=0,5 | 6 | 2,022 |
A Unified Framework for Domain Adaptive Pose Estimation | 9 | eccv | 4 | 1 | 2023-06-17 00:59:51.496000 | https://github.com/visionlearninggroup/uda_poseestimation | 11 | A unified framework for domain adaptive pose estimation | https://scholar.google.com/scholar?cluster=8665350708819483356&hl=en&as_sdt=0,5 | 2 | 2,022 |
A Broad Study of Pre-training for Domain Generalization and Adaptation | 22 | eccv | 2 | 1 | 2023-06-17 00:59:51.709000 | https://github.com/visionlearninggroup/benchmark_domain_transfer | 11 | A broad study of pre-training for domain generalization and adaptation | https://scholar.google.com/scholar?cluster=4743623741984149169&hl=en&as_sdt=0,5 | 2 | 2,022 |
Prior Knowledge Guided Unsupervised Domain Adaptation | 6 | eccv | 1 | 0 | 2023-06-17 00:59:51.920000 | https://github.com/tsun/kuda | 12 | Prior Knowledge Guided Unsupervised Domain Adaptation | https://scholar.google.com/scholar?cluster=16331707540385180374&hl=en&as_sdt=0,5 | 2 | 2,022 |
AcroFOD: An Adaptive Method for Cross-Domain Few-Shot Object Detection | 6 | eccv | 4 | 0 | 2023-06-17 00:59:52.133000 | https://github.com/hlings/acrofod | 30 | AcroFOD: An Adaptive Method for Cross-Domain Few-Shot Object Detection | https://scholar.google.com/scholar?cluster=8976863318013390692&hl=en&as_sdt=0,10 | 2 | 2,022 |
Visual Prompt Tuning | 249 | eccv | 63 | 7 | 2023-06-17 00:59:52.346000 | https://github.com/KMnP/vpt | 561 | Visual prompt tuning | https://scholar.google.com/scholar?cluster=14421942083121350206&hl=en&as_sdt=0,5 | 8 | 2,022 |
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