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MEMO: Test Time Robustness via Adaptation and Augmentation | 63 | neurips | 4 | 1 | 2023-06-16 23:00:44.854000 | https://github.com/zhangmarvin/memo | 34 | Memo: Test time robustness via adaptation and augmentation | https://scholar.google.com/scholar?cluster=1448618539109048791&hl=en&as_sdt=0,11 | 2 | 2,022 |
Asymptotically Unbiased Instance-wise Regularized Partial AUC Optimization: Theory and Algorithm | 0 | neurips | 0 | 0 | 2023-06-16 23:00:45.065000 | https://github.com/shaocr/pauci | 4 | Asymptotically Unbiased Instance-wise Regularized Partial AUC Optimization: Theory and Algorithm | https://scholar.google.com/scholar?cluster=11237720995546922276&hl=en&as_sdt=0,10 | 2 | 2,022 |
Error Correction Code Transformer | 7 | neurips | 6 | 0 | 2023-06-16 23:00:45.281000 | https://github.com/yonilc/ecct | 13 | Error correction code transformer | https://scholar.google.com/scholar?cluster=903759423999065870&hl=en&as_sdt=0,33 | 2 | 2,022 |
Capturing Graphs with Hypo-Elliptic Diffusions | 0 | neurips | 0 | 0 | 2023-06-16 23:00:45.499000 | https://github.com/tgcsaba/graph2tens | 2 | Capturing Graphs with Hypo-Elliptic Diffusions | https://scholar.google.com/scholar?cluster=15681689406304217341&hl=en&as_sdt=0,10 | 1 | 2,022 |
SIXO: Smoothing Inference with Twisted Objectives | 0 | neurips | 0 | 0 | 2023-06-16 23:00:45.712000 | https://github.com/lindermanlab/sixo | 3 | SIXO: Smoothing Inference with Twisted Objectives | https://scholar.google.com/scholar?cluster=12038259047812745507&hl=en&as_sdt=0,34 | 3 | 2,022 |
Exploring evolution-aware & -free protein language models as protein function predictors | 2 | neurips | 8 | 3 | 2023-06-16 16:57:06.093000 | https://github.com/elttaes/revisiting-plms | 40 | On pre-trained language models for antibody | https://scholar.google.com/scholar?cluster=3644203748348349044&hl=en&as_sdt=0,33 | 2 | 2,022 |
Breaking Bad: A Dataset for Geometric Fracture and Reassembly | 4 | neurips | 8 | 0 | 2023-06-16 23:00:45.923000 | https://github.com/wuziyi616/multi_part_assembly | 39 | Breaking Bad: A Dataset for Geometric Fracture and Reassembly | https://scholar.google.com/scholar?cluster=14499530288450300317&hl=en&as_sdt=0,5 | 2 | 2,022 |
Geoclidean: Few-Shot Generalization in Euclidean Geometry | 2 | neurips | 0 | 0 | 2023-06-16 23:00:46.136000 | https://github.com/joyhsu0504/geoclidean_framework | 6 | Geoclidean: Few-shot generalization in euclidean geometry | https://scholar.google.com/scholar?cluster=15302234923717650723&hl=en&as_sdt=0,5 | 2 | 2,022 |
Structural Kernel Search via Bayesian Optimization and Symbolical Optimal Transport | 1 | neurips | 0 | 0 | 2023-06-16 23:00:46.349000 | https://github.com/boschresearch/bosot | 0 | Structural Kernel Search via Bayesian Optimization and Symbolical Optimal Transport | https://scholar.google.com/scholar?cluster=5846774864854783055&hl=en&as_sdt=0,4 | 3 | 2,022 |
Robust Models are less Over-Confident | 1 | neurips | 1 | 0 | 2023-06-16 23:00:46.561000 | https://github.com/gejulia/robustness_confidences_evaluation | 17 | Robust Models are less Over-Confident | https://scholar.google.com/scholar?cluster=11840327885361702172&hl=en&as_sdt=0,33 | 3 | 2,022 |
ComMU: Dataset for Combinatorial Music Generation | 0 | neurips | 24 | 0 | 2023-06-16 23:00:46.773000 | https://github.com/POZAlabs/ComMU-code | 118 | ComMU: Dataset for Combinatorial Music Generation | https://scholar.google.com/scholar?cluster=17767260003172440235&hl=en&as_sdt=0,5 | 6 | 2,022 |
Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition | 83 | eccv | 91 | 0 | 2023-06-16 23:55:11.795000 | https://github.com/XiaohangZhan/cdp | 444 | Consensus-driven propagation in massive unlabeled data for face recognition | https://scholar.google.com/scholar?cluster=3229094614013455360&hl=en&as_sdt=0,43 | 22 | 2,018 |
Deep Cross-Modal Projection Learning for Image-Text Matching | 280 | eccv | 20 | 12 | 2023-06-16 23:55:12.010000 | https://github.com/YingZhangDUT/Cross-Modal-Projection-Learning | 88 | Deep cross-modal projection learning for image-text matching | https://scholar.google.com/scholar?cluster=17800185495041580477&hl=en&as_sdt=0,5 | 2 | 2,018 |
Multi-Class Model Fitting by Energy Minimization and Mode-Seeking | 41 | eccv | 2 | 0 | 2023-06-16 23:55:12.222000 | https://github.com/danini/multi-x | 14 | Multi-class model fitting by energy minimization and mode-seeking | https://scholar.google.com/scholar?cluster=9207771737491685637&hl=en&as_sdt=0,5 | 3 | 2,018 |
Depth Estimation via Affinity Learned with Convolutional Spatial Propagation Network | 261 | eccv | 95 | 25 | 2023-06-16 23:55:12.434000 | https://github.com/XinJCheng/CSPN | 482 | Depth estimation via affinity learned with convolutional spatial propagation network | https://scholar.google.com/scholar?cluster=15331233772685404808&hl=en&as_sdt=0,18 | 20 | 2,018 |
Fast Light Field Reconstruction With Deep Coarse-To-Fine Modeling of Spatial-Angular Clues | 121 | eccv | 9 | 2 | 2023-06-16 23:55:12.645000 | https://github.com/angularsr/LightFieldAngularSR | 16 | Fast light field reconstruction with deep coarse-to-fine modeling of spatial-angular clues | https://scholar.google.com/scholar?cluster=2431722100986178790&hl=en&as_sdt=0,5 | 2 | 2,018 |
Deep Expander Networks: Efficient Deep Networks from Graph Theory | 68 | eccv | 12 | 0 | 2023-06-16 23:55:12.856000 | https://github.com/DrImpossible/Deep-Expander-Networks | 43 | Deep expander networks: Efficient deep networks from graph theory | https://scholar.google.com/scholar?cluster=14046312150868626891&hl=en&as_sdt=0,5 | 4 | 2,018 |
Attend and Rectify: a gated attention mechanism for fine-grained recovery | 45 | eccv | 10 | 2 | 2023-06-16 23:55:13.067000 | https://github.com/prlz77/attend-and-rectify | 52 | Attend and rectify: a gated attention mechanism for fine-grained recovery | https://scholar.google.com/scholar?cluster=13738598675286043975&hl=en&as_sdt=0,34 | 4 | 2,018 |
PyramidBox: A Context-assisted Single Shot Face Detector | 369 | eccv | 2,965 | 869 | 2023-06-16 23:55:13.279000 | https://github.com/PaddlePaddle/models | 6,794 | Pyramidbox: A context-assisted single shot face detector | https://scholar.google.com/scholar?cluster=15584112941596045225&hl=en&as_sdt=0,10 | 275 | 2,018 |
Learning to Blend Photos | 9 | eccv | 1 | 3 | 2023-06-16 23:55:13.490000 | https://github.com/hfslyc/LearnToBlend | 51 | Learning to blend photos | https://scholar.google.com/scholar?cluster=3769330447198783594&hl=en&as_sdt=0,5 | 11 | 2,018 |
Parallel Feature Pyramid Network for Object Detection | 265 | eccv | 0 | 1 | 2023-06-16 23:55:13.702000 | https://github.com/chosj95/PFPNet.pytorch | 7 | Parallel feature pyramid network for object detection | https://scholar.google.com/scholar?cluster=3087633766276723421&hl=en&as_sdt=0,44 | 4 | 2,018 |
AMC: AutoML for Model Compression and Acceleration on Mobile Devices | 1,290 | eccv | 101 | 18 | 2023-06-16 23:55:13.914000 | https://github.com/mit-han-lab/amc | 389 | Amc: Automl for model compression and acceleration on mobile devices | https://scholar.google.com/scholar?cluster=2282234460810497997&hl=en&as_sdt=0,5 | 17 | 2,018 |
Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes | 4 | eccv | 0 | 0 | 2023-06-16 23:55:14.126000 | https://github.com/SSAW14/Image_Generation_with_Latent_Code | 5 | Diverse conditional image generation by stochastic regression with latent drop-out codes | https://scholar.google.com/scholar?cluster=12901521834315921854&hl=en&as_sdt=0,39 | 3 | 2,018 |
PS-FCN: A Flexible Learning Framework for Photometric Stereo | 125 | eccv | 31 | 0 | 2023-06-16 23:55:14.336000 | https://github.com/guanyingc/PS-FCN | 81 | PS-FCN: A flexible learning framework for photometric stereo | https://scholar.google.com/scholar?cluster=2638846704814041836&hl=en&as_sdt=0,36 | 6 | 2,018 |
Instance-level Human Parsing via Part Grouping Network | 294 | eccv | 101 | 38 | 2023-06-16 23:55:14.547000 | https://github.com/Engineering-Course/CIHP_PGN | 381 | Instance-level human parsing via part grouping network | https://scholar.google.com/scholar?cluster=9349119763164764615&hl=en&as_sdt=0,41 | 17 | 2,018 |
Constrained Optimization Based Low-Rank Approximation of Deep Neural Networks | 62 | eccv | 1 | 0 | 2023-06-16 23:55:14.759000 | https://github.com/chongli-uw/cobla | 2 | Constrained optimization based low-rank approximation of deep neural networks | https://scholar.google.com/scholar?cluster=16361848153367526892&hl=en&as_sdt=0,14 | 2 | 2,018 |
CTAP: Complementary Temporal Action Proposal Generation | 183 | eccv | 11 | 6 | 2023-06-16 23:55:14.969000 | https://github.com/jiyanggao/CTAP | 42 | Ctap: Complementary temporal action proposal generation | https://scholar.google.com/scholar?cluster=6089124584810492910&hl=en&as_sdt=0,3 | 5 | 2,018 |
Dist-GAN: An Improved GAN using Distance Constraints | 92 | eccv | 21 | 5 | 2023-06-16 23:55:15.180000 | https://github.com/tntrung/gan | 66 | Dist-gan: An improved gan using distance constraints | https://scholar.google.com/scholar?cluster=14413655732899864103&hl=en&as_sdt=0,10 | 5 | 2,018 |
Towards End-to-End License Plate Detection and Recognition: A Large Dataset and Baseline | 235 | eccv | 559 | 84 | 2023-06-16 23:55:15.391000 | https://github.com/detectRecog/CCPD | 1,964 | Towards end-to-end license plate detection and recognition: A large dataset and baseline | https://scholar.google.com/scholar?cluster=14804408137924957473&hl=en&as_sdt=0,5 | 63 | 2,018 |
Cross-Modal and Hierarchical Modeling of Video and Text | 115 | eccv | 6 | 2 | 2023-06-16 23:55:15.648000 | https://github.com/Sha-Lab/CMHSE | 17 | Cross-modal and hierarchical modeling of video and text | https://scholar.google.com/scholar?cluster=4253130459603491568&hl=en&as_sdt=0,5 | 5 | 2,018 |
StarMap for Category-Agnostic Keypoint and Viewpoint Estimation | 70 | eccv | 18 | 5 | 2023-06-16 23:55:15.858000 | https://github.com/xingyizhou/StarMap | 101 | Starmap for category-agnostic keypoint and viewpoint estimation | https://scholar.google.com/scholar?cluster=182684951534940435&hl=en&as_sdt=0,5 | 10 | 2,018 |
Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization | 176 | eccv | 0 | 1 | 2023-06-16 23:55:16.069000 | https://github.com/danieljakubovitz/Jacobian_Regularization | 3 | Improving dnn robustness to adversarial attacks using jacobian regularization | https://scholar.google.com/scholar?cluster=15145149459046831045&hl=en&as_sdt=0,5 | 1 | 2,018 |
Folded Recurrent Neural Networks for Future Video Prediction | 103 | eccv | 12 | 2 | 2023-06-16 23:55:16.280000 | https://github.com/moliusimon/frnn | 39 | Folded recurrent neural networks for future video prediction | https://scholar.google.com/scholar?cluster=14311378408238305215&hl=en&as_sdt=0,5 | 2 | 2,018 |
Look Before You Leap: Bridging Model-Free and Model-Based Reinforcement Learning for Planned-Ahead Vision-and-Language Navigation | 200 | eccv | 120 | 41 | 2023-06-16 23:55:16.491000 | https://github.com/peteanderson80/Matterport3DSimulator | 378 | Look before you leap: Bridging model-free and model-based reinforcement learning for planned-ahead vision-and-language navigation | https://scholar.google.com/scholar?cluster=4362703551818063501&hl=en&as_sdt=0,28 | 19 | 2,018 |
Acquisition of Localization Confidence for Accurate Object Detection | 841 | eccv | 151 | 20 | 2023-06-16 23:55:16.703000 | https://github.com/vacancy/PreciseRoIPooling | 761 | Acquisition of localization confidence for accurate object detection | https://scholar.google.com/scholar?cluster=14154791864857863721&hl=en&as_sdt=0,31 | 24 | 2,018 |
Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network | 691 | eccv | 940 | 164 | 2023-06-16 23:55:16.914000 | https://github.com/YadiraF/PRNet | 4,799 | Joint 3d face reconstruction and dense alignment with position map regression network | https://scholar.google.com/scholar?cluster=2161439188175601394&hl=en&as_sdt=0,26 | 190 | 2,018 |
Multimodal Unsupervised Image-to-image Translation | 2,289 | eccv | 484 | 61 | 2023-06-16 23:55:17.125000 | https://github.com/nvlabs/MUNIT | 2,565 | Multimodal unsupervised image-to-image translation | https://scholar.google.com/scholar?cluster=13317525907573308290&hl=en&as_sdt=0,6 | 76 | 2,018 |
Diverse feature visualizations reveal invariances in early layers of deep neural networks | 25 | eccv | 0 | 0 | 2023-06-16 23:55:17.336000 | https://github.com/sacadena/diverse_feature_vis | 5 | Diverse feature visualizations reveal invariances in early layers of deep neural networks | https://scholar.google.com/scholar?cluster=5475890318105532537&hl=en&as_sdt=0,5 | 5 | 2,018 |
Learning Dynamic Memory Networks for Object Tracking | 285 | eccv | 12 | 4 | 2023-06-16 23:55:17.547000 | https://github.com/skyoung/MemTrack | 81 | Learning dynamic memory networks for object tracking | https://scholar.google.com/scholar?cluster=5536802084548288754&hl=en&as_sdt=0,36 | 9 | 2,018 |
Statistically-motivated Second-order Pooling | 51 | eccv | 2 | 1 | 2023-06-16 23:55:17.758000 | https://github.com/kcyu2014/smsop | 32 | Statistically-motivated second-order pooling | https://scholar.google.com/scholar?cluster=12417165649470483444&hl=en&as_sdt=0,39 | 5 | 2,018 |
Improving Generalization via Scalable Neighborhood Component Analysis | 125 | eccv | 0 | 0 | 2023-06-16 23:55:17.969000 | https://github.com/zhirongw/snca.pytorch | 8 | Improving generalization via scalable neighborhood component analysis | https://scholar.google.com/scholar?cluster=1930762472534444949&hl=en&as_sdt=0,5 | 2 | 2,018 |
Distractor-aware Siamese Networks for Visual Object Tracking | 1,214 | eccv | 360 | 31 | 2023-06-16 23:55:18.181000 | https://github.com/foolwood/DaSiamRPN | 1,228 | Distractor-aware siamese networks for visual object tracking | https://scholar.google.com/scholar?cluster=5659298886572595606&hl=en&as_sdt=0,46 | 56 | 2,018 |
Escaping from Collapsing Modes in a Constrained Space | 16 | eccv | 1 | 0 | 2023-06-16 23:55:18.392000 | https://github.com/chang810249/BEGAN-CS | 12 | Escaping from collapsing modes in a constrained space | https://scholar.google.com/scholar?cluster=8912424288441556924&hl=en&as_sdt=0,10 | 2 | 2,018 |
Discriminative Region Proposal Adversarial Networks for High-Quality Image-to-Image Translation | 53 | eccv | 9 | 6 | 2023-06-16 23:55:18.615000 | https://github.com/godisboy/DRPAN | 51 | Discriminative region proposal adversarial networks for high-quality image-to-image translation | https://scholar.google.com/scholar?cluster=3209031446584734295&hl=en&as_sdt=0,5 | 6 | 2,018 |
Learning Blind Video Temporal Consistency | 252 | eccv | 62 | 14 | 2023-06-16 23:55:18.826000 | https://github.com/phoenix104104/fast_blind_video_consistency | 367 | Learning blind video temporal consistency | https://scholar.google.com/scholar?cluster=7698730627265999813&hl=en&as_sdt=0,50 | 9 | 2,018 |
Graph Distillation for Action Detection with Privileged Modalities | 100 | eccv | 18 | 3 | 2023-06-16 23:55:19.037000 | https://github.com/google/graph_distillation | 64 | Graph distillation for action detection with privileged modalities | https://scholar.google.com/scholar?cluster=11357384495865637099&hl=en&as_sdt=0,5 | 6 | 2,018 |
Efficient Uncertainty Estimation for Semantic Segmentation in Videos | 99 | eccv | 8 | 2 | 2023-06-16 23:55:19.249000 | https://github.com/andyhahaha/Efficient-Uncertainty-Video-Segmentation | 22 | Efficient uncertainty estimation for semantic segmentation in videos | https://scholar.google.com/scholar?cluster=12752926199091689307&hl=en&as_sdt=0,5 | 4 | 2,018 |
Seeing Deeply and Bidirectionally: A Deep Learning Approach for Single Image Reflection Removal | 131 | eccv | 12 | 5 | 2023-06-16 23:55:19.460000 | https://github.com/yangj1e/bdn-refremv | 46 | Seeing deeply and bidirectionally: A deep learning approach for single image reflection removal | https://scholar.google.com/scholar?cluster=10372612231120248014&hl=en&as_sdt=0,5 | 7 | 2,018 |
Learning SO(3) Equivariant Representations with Spherical CNNs | 424 | eccv | 48 | 6 | 2023-06-16 23:55:19.671000 | https://github.com/daniilidis-group/spherical-cnn | 275 | Learning so (3) equivariant representations with spherical cnns | https://scholar.google.com/scholar?cluster=13360112200606529500&hl=en&as_sdt=0,5 | 14 | 2,018 |
T2Net: Synthetic-to-Realistic Translation for Solving Single-Image Depth Estimation Tasks | 162 | eccv | 41 | 8 | 2023-06-16 23:55:19.882000 | https://github.com/lyndonzheng/Synthetic2Realistic | 177 | T2net: Synthetic-to-realistic translation for solving single-image depth estimation tasks | https://scholar.google.com/scholar?cluster=2045753887928749430&hl=en&as_sdt=0,5 | 6 | 2,018 |
Partial Adversarial Domain Adaptation | 384 | eccv | 41 | 1 | 2023-06-16 23:55:20.094000 | https://github.com/thuml/PADA | 90 | Partial adversarial domain adaptation | https://scholar.google.com/scholar?cluster=5435435641375957692&hl=en&as_sdt=0,33 | 11 | 2,018 |
Diverse Image-to-Image Translation via Disentangled Representations | 1,135 | eccv | 153 | 30 | 2023-06-16 23:55:20.305000 | https://github.com/HsinYingLee/DRIT | 810 | Diverse image-to-image translation via disentangled representations | https://scholar.google.com/scholar?cluster=2272463241175511122&hl=en&as_sdt=0,20 | 15 | 2,018 |
BOP: Benchmark for 6D Object Pose Estimation | 334 | eccv | 112 | 7 | 2023-06-16 23:55:20.515000 | https://github.com/thodan/bop_toolkit | 287 | Bop: Benchmark for 6d object pose estimation | https://scholar.google.com/scholar?cluster=7913199704113527&hl=en&as_sdt=0,5 | 11 | 2,018 |
Generative Domain-Migration Hashing for Sketch-to-Image Retrieval | 85 | eccv | 6 | 3 | 2023-06-16 23:55:20.726000 | https://github.com/YCJGG/GDH | 21 | Generative domain-migration hashing for sketch-to-image retrieval | https://scholar.google.com/scholar?cluster=11613774012144257188&hl=en&as_sdt=0,5 | 2 | 2,018 |
FloorNet: A Unified Framework for Floorplan Reconstruction from 3D Scans | 122 | eccv | 49 | 15 | 2023-06-16 23:55:20.936000 | https://github.com/art-programmer/FloorNet | 189 | Floornet: A unified framework for floorplan reconstruction from 3d scans | https://scholar.google.com/scholar?cluster=6050985589125390059&hl=en&as_sdt=0,5 | 12 | 2,018 |
DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency | 442 | eccv | 33 | 4 | 2023-06-16 23:55:21.147000 | https://github.com/vt-vl-lab/DF-Net | 209 | Df-net: Unsupervised joint learning of depth and flow using cross-task consistency | https://scholar.google.com/scholar?cluster=14124367292083542005&hl=en&as_sdt=0,6 | 9 | 2,018 |
Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition | 278 | eccv | 23 | 7 | 2023-06-16 23:55:21.358000 | https://github.com/ChaojianYu/Hierarchical-Bilinear-Pooling | 102 | Hierarchical bilinear pooling for fine-grained visual recognition | https://scholar.google.com/scholar?cluster=4033149798374032404&hl=en&as_sdt=0,5 | 1 | 2,018 |
Face De-Spoofing: Anti-Spoofing via Noise Modeling | 265 | eccv | 42 | 15 | 2023-06-16 23:55:21.569000 | https://github.com/yaojieliu/ECCV2018-FaceDeSpoofing | 143 | Face de-spoofing: Anti-spoofing via noise modeling | https://scholar.google.com/scholar?cluster=6923482401871998322&hl=en&as_sdt=0,23 | 8 | 2,018 |
Efficient Relative Attribute Learning using Graph Neural Networks | 30 | eccv | 4 | 1 | 2023-06-16 23:55:21.780000 | https://github.com/zihangm/RAL_GNN | 20 | Efficient relative attribute learning using graph neural networks | https://scholar.google.com/scholar?cluster=11106726889748018924&hl=en&as_sdt=0,5 | 0 | 2,018 |
Localization Recall Precision (LRP): A New Performance Metric for Object Detection | 115 | eccv | 13 | 0 | 2023-06-16 23:55:21.992000 | https://github.com/cancam/LRP | 63 | Localization recall precision (LRP): A new performance metric for object detection | https://scholar.google.com/scholar?cluster=18184659199813329105&hl=en&as_sdt=0,5 | 8 | 2,018 |
Image Super-Resolution Using Very Deep Residual Channel Attention Networks | 3,523 | eccv | 319 | 76 | 2023-06-16 23:55:22.204000 | https://github.com/yulunzhang/RCAN | 1,245 | Image super-resolution using very deep residual channel attention networks | https://scholar.google.com/scholar?cluster=3748973811121591896&hl=en&as_sdt=0,10 | 21 | 2,018 |
Extending Layered Models to 3D Motion | 32 | eccv | 0 | 0 | 2023-06-16 23:55:22.414000 | https://github.com/donglao/layers3Dmotion | 2 | Extending layered models to 3d motion | https://scholar.google.com/scholar?cluster=3699102061773173844&hl=en&as_sdt=0,25 | 3 | 2,018 |
License Plate Detection and Recognition in Unconstrained Scenarios | 268 | eccv | 595 | 112 | 2023-06-16 23:55:22.641000 | https://github.com/sergiomsilva/alpr-unconstrained | 1,623 | License plate detection and recognition in unconstrained scenarios | https://scholar.google.com/scholar?cluster=12853420144391201059&hl=en&as_sdt=0,5 | 87 | 2,018 |
ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking | 85 | eccv | 10 | 8 | 2023-06-16 23:55:22.851000 | https://github.com/ogroth/shapestacks | 41 | Shapestacks: Learning vision-based physical intuition for generalised object stacking | https://scholar.google.com/scholar?cluster=11796899814392889836&hl=en&as_sdt=0,5 | 5 | 2,018 |
SRDA: Generating Instance Segmentation Annotation via Scanning, Reasoning and Domain Adaptation | 19 | eccv | 1 | 0 | 2023-06-16 23:55:23.064000 | https://github.com/DirtyHarryLYL/SRDA-ECCV2018 | 7 | Srda: Generating instance segmentation annotation via scanning, reasoning and domain adaptation | https://scholar.google.com/scholar?cluster=14701934472659497490&hl=en&as_sdt=0,5 | 2 | 2,018 |
On the Solvability of Viewing Graphs | 10 | eccv | 0 | 0 | 2023-06-16 23:55:23.278000 | https://github.com/mtrager/viewing-graphs | 1 | On the solvability of viewing graphs | https://scholar.google.com/scholar?cluster=11272659149049993124&hl=en&as_sdt=0,5 | 2 | 2,018 |
A Systematic DNN Weight Pruning Framework using Alternating Direction Method of Multipliers | 390 | eccv | 33 | 6 | 2023-06-16 23:55:23.490000 | https://github.com/KaiqiZhang/admm-pruning | 95 | A systematic dnn weight pruning framework using alternating direction method of multipliers | https://scholar.google.com/scholar?cluster=17353545770360369624&hl=en&as_sdt=0,5 | 8 | 2,018 |
Single Shot Scene Text Retrieval | 42 | eccv | 30 | 1 | 2023-06-16 23:55:23.702000 | https://github.com/lluisgomez/single-shot-str | 66 | Single shot scene text retrieval | https://scholar.google.com/scholar?cluster=18342223451780815542&hl=en&as_sdt=0,5 | 10 | 2,018 |
Deep Shape Matching | 76 | eccv | 47 | 5 | 2023-06-16 23:55:23.922000 | https://github.com/janesjanes/sketchy | 157 | Deep shape matching | https://scholar.google.com/scholar?cluster=8039392131029835381&hl=en&as_sdt=0,33 | 6 | 2,018 |
Learning to Navigate for Fine-grained Classification | 462 | eccv | 119 | 38 | 2023-06-16 23:55:24.134000 | https://github.com/yangze0930/NTS-Net | 435 | Learning to navigate for fine-grained classification | https://scholar.google.com/scholar?cluster=14152137546438136393&hl=en&as_sdt=0,5 | 11 | 2,018 |
Improving Shape Deformation in Unsupervised Image-to-Image Translation | 80 | eccv | 22 | 17 | 2023-06-16 23:55:24.347000 | https://github.com/brownvc/ganimorph | 119 | Improving shape deformation in unsupervised image-to-image translation | https://scholar.google.com/scholar?cluster=8740306489765068872&hl=en&as_sdt=0,5 | 17 | 2,018 |
LSQ++: Lower running time and higher recall in multi-codebook quantization | 31 | eccv | 4 | 27 | 2023-06-16 23:55:24.565000 | https://github.com/una-dinosauria/Rayuela.jl | 57 | LSQ++: Lower running time and higher recall in multi-codebook quantization | https://scholar.google.com/scholar?cluster=2638321853527220522&hl=en&as_sdt=0,11 | 5 | 2,018 |
Depth-aware CNN for RGB-D Segmentation | 240 | eccv | 83 | 34 | 2023-06-16 23:55:24.802000 | https://github.com/laughtervv/DepthAwareCNN | 292 | Depth-aware cnn for rgb-d segmentation | https://scholar.google.com/scholar?cluster=13093843379314761716&hl=en&as_sdt=0,23 | 14 | 2,018 |
Weakly- and Semi-Supervised Panoptic Segmentation | 177 | eccv | 24 | 0 | 2023-06-16 23:55:25.039000 | https://github.com/qizhuli/Weakly-Supervised-Panoptic-Segmentation | 159 | Weakly-and semi-supervised panoptic segmentation | https://scholar.google.com/scholar?cluster=7210150945066091860&hl=en&as_sdt=0,41 | 12 | 2,018 |
Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field Estimation | 79 | eccv | 20 | 3 | 2023-06-16 23:55:25.251000 | https://github.com/NVlabs/learningrigidity | 143 | Learning rigidity in dynamic scenes with a moving camera for 3d motion field estimation | https://scholar.google.com/scholar?cluster=827835377637646447&hl=en&as_sdt=0,10 | 17 | 2,018 |
Textual Explanations for Self-Driving Vehicles | 214 | eccv | 14 | 9 | 2023-06-16 23:55:25.463000 | https://github.com/JinkyuKimUCB/explainable-deep-driving | 51 | Textual explanations for self-driving vehicles | https://scholar.google.com/scholar?cluster=3588149335447094159&hl=en&as_sdt=0,5 | 4 | 2,018 |
Shuffle-Then-Assemble: Learning Object-Agnostic Visual Relationship Features | 79 | eccv | 30 | 19 | 2023-06-16 23:55:25.674000 | https://github.com/yangxuntu/vrd | 90 | Shuffle-then-assemble: Learning object-agnostic visual relationship features | https://scholar.google.com/scholar?cluster=11457586717303926687&hl=en&as_sdt=0,5 | 4 | 2,018 |
Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors | 67 | eccv | 21 | 2 | 2023-06-16 23:55:25.885000 | https://github.com/dbaranchuk/ivf-hnsw | 163 | Revisiting the inverted indices for billion-scale approximate nearest neighbors | https://scholar.google.com/scholar?cluster=17143188662932206713&hl=en&as_sdt=0,33 | 6 | 2,018 |
Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection | 441 | eccv | 27 | 7 | 2023-06-16 23:55:26.096000 | https://github.com/shenjianbing/PDB-ConvLSTM | 113 | Pyramid dilated deeper convlstm for video salient object detection | https://scholar.google.com/scholar?cluster=4923326738440851048&hl=en&as_sdt=0,32 | 9 | 2,018 |
Beyond local reasoning for stereo confidence estimation with deep learning | 59 | eccv | 5 | 1 | 2023-06-16 23:55:26.308000 | https://github.com/fabiotosi92/LGC-Tensorflow | 10 | Beyond local reasoning for stereo confidence estimation with deep learning | https://scholar.google.com/scholar?cluster=15944809692028106974&hl=en&as_sdt=0,23 | 3 | 2,018 |
Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights | 487 | eccv | 23 | 2 | 2023-06-16 23:55:26.518000 | https://github.com/arunmallya/piggyback | 172 | Piggyback: Adapting a single network to multiple tasks by learning to mask weights | https://scholar.google.com/scholar?cluster=14326835779502008295&hl=en&as_sdt=0,5 | 4 | 2,018 |
PSANet: Point-wise Spatial Attention Network for Scene Parsing | 918 | eccv | 37 | 1 | 2023-06-16 23:55:26.730000 | https://github.com/hszhao/PSANet | 216 | Psanet: Point-wise spatial attention network for scene parsing | https://scholar.google.com/scholar?cluster=5612902286487550404&hl=en&as_sdt=0,5 | 12 | 2,018 |
SkipNet: Learning Dynamic Routing in Convolutional Networks | 561 | eccv | 47 | 7 | 2023-06-16 23:55:26.941000 | https://github.com/ucbdrive/skipnet | 223 | Skipnet: Learning dynamic routing in convolutional networks | https://scholar.google.com/scholar?cluster=16831193156348049998&hl=en&as_sdt=0,18 | 14 | 2,018 |
The Contextual Loss for Image Transformation with Non-Aligned Data | 333 | eccv | 78 | 13 | 2023-06-16 23:55:27.151000 | https://github.com/roimehrez/contextualLoss | 472 | The contextual loss for image transformation with non-aligned data | https://scholar.google.com/scholar?cluster=4201014753742149913&hl=en&as_sdt=0,19 | 19 | 2,018 |
Fully-Convolutional Point Networks for Large-Scale Point Clouds | 180 | eccv | 23 | 3 | 2023-06-16 23:55:27.362000 | https://github.com/drethage/fully-convolutional-point-network | 86 | Fully-convolutional point networks for large-scale point clouds | https://scholar.google.com/scholar?cluster=15796798606510706475&hl=en&as_sdt=0,30 | 13 | 2,018 |
Integral Human Pose Regression | 725 | eccv | 75 | 10 | 2023-06-16 23:55:27.573000 | https://github.com/JimmySuen/integral-human-pose | 456 | Integral human pose regression | https://scholar.google.com/scholar?cluster=13367121804975374310&hl=en&as_sdt=0,5 | 25 | 2,018 |
A Dataset and Architecture for Visual Reasoning with a Working Memory | 51 | eccv | 13 | 0 | 2023-06-16 23:55:27.784000 | https://github.com/google/cog | 41 | A dataset and architecture for visual reasoning with a working memory | https://scholar.google.com/scholar?cluster=7092743520972213867&hl=en&as_sdt=0,3 | 7 | 2,018 |
Affinity Derivation and Graph Merge for Instance Segmentation | 103 | eccv | 8 | 3 | 2023-06-16 23:55:27.995000 | https://github.com/xck36/GMIS | 39 | Affinity derivation and graph merge for instance segmentation | https://scholar.google.com/scholar?cluster=10478540241382688376&hl=en&as_sdt=0,11 | 4 | 2,018 |
Modality Distillation with Multiple Stream Networks for Action Recognition | 154 | eccv | 3 | 3 | 2023-06-16 23:55:28.207000 | https://github.com/ncgarcia/modality-distillation | 21 | Modality distillation with multiple stream networks for action recognition | https://scholar.google.com/scholar?cluster=11766651177768406473&hl=en&as_sdt=0,11 | 4 | 2,018 |
Unsupervised Domain Adaptation for 3D Keypoint Estimation via View Consistency | 33 | eccv | 7 | 3 | 2023-06-16 23:55:28.418000 | https://github.com/xingyizhou/3DKeypoints-DA | 82 | Unsupervised domain adaptation for 3d keypoint estimation via view consistency | https://scholar.google.com/scholar?cluster=10330474330891828727&hl=en&as_sdt=0,14 | 11 | 2,018 |
Group Normalization | 3,074 | eccv | 20 | 1 | 2023-06-16 23:55:28.643000 | https://github.com/ppwwyyxx/GroupNorm-reproduce | 113 | Group normalization | https://scholar.google.com/scholar?cluster=14814179610283147593&hl=en&as_sdt=0,5 | 6 | 2,018 |
Conditional Image-Text Embedding Networks | 103 | eccv | 91 | 1 | 2023-06-16 23:55:28.855000 | https://github.com/BryanPlummer/cite | 38 | Conditional image-text embedding networks | https://scholar.google.com/scholar?cluster=16144402408937710486&hl=en&as_sdt=0,44 | 2 | 2,018 |
Object Level Visual Reasoning in Videos | 161 | eccv | 20 | 5 | 2023-06-16 23:55:29.066000 | https://github.com/fabienbaradel/object_level_visual_reasoning | 172 | Object level visual reasoning in videos | https://scholar.google.com/scholar?cluster=17632579279713545301&hl=en&as_sdt=0,5 | 15 | 2,018 |
Deep Clustering for Unsupervised Learning of Visual Features | 2,326 | eccv | 310 | 8 | 2023-06-16 23:55:29.277000 | https://github.com/facebookresearch/deepcluster | 1,549 | Deep clustering for unsupervised learning of visual features | https://scholar.google.com/scholar?cluster=9776210521429980111&hl=en&as_sdt=0,10 | 33 | 2,018 |
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models | 364 | eccv | 21 | 1 | 2023-06-16 23:55:29.488000 | https://github.com/huanzhang12/Adversarial_Survey | 98 | Is Robustness the Cost of Accuracy?--A Comprehensive Study on the Robustness of 18 Deep Image Classification Models | https://scholar.google.com/scholar?cluster=380810929013428531&hl=en&as_sdt=0,5 | 8 | 2,018 |
Single Image Water Hazard Detection using FCN with Reflection Attention Units | 30 | eccv | 16 | 12 | 2023-06-16 23:55:29.700000 | https://github.com/Cow911/SingleImageWaterHazardDetectionWithRAU | 50 | Single image water hazard detection using fcn with reflection attention units | https://scholar.google.com/scholar?cluster=7504719303538721682&hl=en&as_sdt=0,44 | 4 | 2,018 |
Predicting Gaze in Egocentric Video by Learning Task-dependent Attention Transition | 103 | eccv | 18 | 1 | 2023-06-16 23:55:29.911000 | https://github.com/hyf015/egocentric-gaze-prediction | 55 | Predicting gaze in egocentric video by learning task-dependent attention transition | https://scholar.google.com/scholar?cluster=1151610918319195215&hl=en&as_sdt=0,24 | 4 | 2,018 |
Joint Learning of Intrinsic Images and Semantic Segmentation | 43 | eccv | 1 | 1 | 2023-06-16 23:55:30.123000 | https://github.com/Morpheus3000/intrinseg | 12 | Joint learning of intrinsic images and semantic segmentation | https://scholar.google.com/scholar?cluster=76148957542870676&hl=en&as_sdt=0,11 | 2 | 2,018 |
Bidirectional Feature Pyramid Network with Recurrent Attention Residual Modules for Shadow Detection | 183 | eccv | 26 | 13 | 2023-06-16 23:55:30.335000 | https://github.com/zijundeng/BDRAR | 112 | Bidirectional feature pyramid network with recurrent attention residual modules for shadow detection | https://scholar.google.com/scholar?cluster=9596477260782472154&hl=en&as_sdt=0,5 | 7 | 2,018 |
Deep Regression Tracking with Shrinkage Loss | 238 | eccv | 14 | 2 | 2023-06-16 23:55:30.546000 | https://github.com/chaoma99/DSLT | 58 | Deep regression tracking with shrinkage loss | https://scholar.google.com/scholar?cluster=13852835873107246854&hl=en&as_sdt=0,14 | 9 | 2,018 |
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