論文速遞2022.10.11！
最新成果demo展示：
代碼：https://github.com/krisnarengga/yolov7-image-segmentation
配置好環(huán)境后運(yùn)行指令：python segment/predict_counting.py --weights yolov7-seg.pt --source 120.mp4 --view-img --nosave --trk
最新論文整理
ECCV2022
Updated on : 11 Oct 2022
total number : 10
SCAM! Transferring humans between images with Semantic Cross Attention Modulation
論文/Paper: http://arxiv.org/pdf/2210.04883
代碼/Code: None
Using Whole Slide Image Representations from Self-Supervised Contrastive Learning for Melanoma Concordance Regression
論文/Paper: http://arxiv.org/pdf/2210.04803
代碼/Code: None
BoundaryFace: A mining framework with noise label self-correction for Face Recognition
論文/Paper: http://arxiv.org/pdf/2210.04567
代碼/Code: https://github.com/swjtu-3dvision/boundaryface
Self-Supervised 3D Human Pose Estimation in Static Video Via Neural Rendering
論文/Paper: http://arxiv.org/pdf/2210.04514
代碼/Code: None
Students taught by multimodal teachers are superior action recognizers
論文/Paper: http://arxiv.org/pdf/2210.04331
代碼/Code: None
Attention Diversification for Domain Generalization
論文/Paper: http://arxiv.org/pdf/2210.04206
代碼/Code: https://github.com/hikvision-research/domaingeneralization
Fast-ParC: Position Aware Global Kernel for ConvNets and ViTs
論文/Paper: http://arxiv.org/pdf/2210.04020
代碼/Code: None
FBNet: Feedback Network for Point Cloud Completion
論文/Paper: http://arxiv.org/pdf/2210.03974
代碼/Code: https://github.com/hikvision-research/3dvision
Super-Resolution by Predicting Offsets: An Ultra-Efficient Super-Resolution Network for Rasterized Images
論文/Paper: http://arxiv.org/pdf/2210.04198
代碼/Code: None
Strong Gravitational Lensing Parameter Estimation with Vision Transformer
論文/Paper: http://arxiv.org/pdf/2210.04143
代碼/Code: https://github.com/kuanweih/strong_lensing_vit_resnet
CVPR2022
NeurIPS
Updated on : 11 Oct 2022
total number : 17
4D Unsupervised Object Discovery
論文/Paper: http://arxiv.org/pdf/2210.04801
代碼/Code: https://github.com/robertwyq/lsmol
OGC: Unsupervised 3D Object Segmentation from Rigid Dynamics of Point Clouds
論文/Paper: http://arxiv.org/pdf/2210.04458
代碼/Code: https://github.com/vlar-group/ogc
Semi-supervised Semantic Segmentation with Prototype-based Consistency Regularization
論文/Paper: http://arxiv.org/pdf/2210.04388
代碼/Code: https://github.com/heimingx/semi_seg_proto
CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds
論文/Paper: http://arxiv.org/pdf/2210.04264
代碼/Code: https://github.com/haiyang-w/cagroup3d
Transformer-based Flood Scene Segmentation for Developing Countries
論文/Paper: http://arxiv.org/pdf/2210.04218
代碼/Code: None
Let Images Give You More:Point Cloud Cross-Modal Training for Shape Analysis
論文/Paper: http://arxiv.org/pdf/2210.04208
代碼/Code: https://github.com/zhanheshen/pointcmt
Coded Residual Transform for Generalizable Deep Metric Learning
論文/Paper: http://arxiv.org/pdf/2210.04180
代碼/Code: None
Stimulative Training of Residual Networks: A Social Psychology Perspective of Loafing
論文/Paper: http://arxiv.org/pdf/2210.04153
代碼/Code: https://github.com/Sunshine-Ye/NIPS22-ST
Robust Graph Structure Learning over Images via Multiple Statistical Tests
論文/Paper: http://arxiv.org/pdf/2210.03956
代碼/Code: https://github.com/thomas-wyh/b-attention
Contact-aware Human Motion Forecasting
論文/Paper: http://arxiv.org/pdf/2210.03954
代碼/Code: https://github.com/wei-mao-2019/contawaremotionpred
EgoTaskQA: Understanding Human Tasks in Egocentric Videos
論文/Paper: http://arxiv.org/pdf/2210.03929
代碼/Code: None
ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints
論文/Paper: http://arxiv.org/pdf/2210.03895
代碼/Code: https://github.com/heathcliff-saku/viewfool_
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings
論文/Paper: http://arxiv.org/pdf/2210.04620
代碼/Code: https://github.com/owkin/flamby
Grow and Merge: A Unified Framework for Continuous Categories Discovery
論文/Paper: http://arxiv.org/pdf/2210.04174
代碼/Code: None
Few-Shot Continual Active Learning by a Robot
論文/Paper: http://arxiv.org/pdf/2210.04137
代碼/Code: None
Meta-DMoE: Adapting to Domain Shift by Meta-Distillation from Mixture-of-Experts
論文/Paper: http://arxiv.org/pdf/2210.03885
代碼/Code: https://github.com/n3il666/Meta-DMoE.
In What Ways Are Deep Neural Networks Invariant and How Should We Measure This?
論文/Paper: http://arxiv.org/pdf/2210.03773
代碼/Code: None