ECCV2022 &CVPR2022论文速递2022.7.19!
最新成果demo展示:
ECCV2022 | XMem: 高质量长期视频分割!
效果超群!
标题:XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
论文:https://arxiv.org/pdf/2207.07115.pdf
代码:https://github.com/hkchengrex/XMem
摘要:
我们提出了 XMem,这是一种用于长视频的视频对象分割架构,具有统一的特征内存存储,受 Atkinson-Shiffrin 内存模型的启发。先前关于视频对象分割的工作通常只使用一种类型的特征记忆。对于超过一分钟的视频,单个特征内存模型将内存消耗和准确性紧密联系在一起。相比之下,遵循 Atkinson-Shiffrin 模型,我们开发了一种架构,该架构包含多个独立但深度连接的特征记忆存储:快速更新的感觉记忆、高分辨率工作记忆和紧凑的持续长期记忆。至关重要的是,我们开发了一种记忆增强算法,该算法通常将积极使用的工作记忆元素整合到长期记忆中,从而避免记忆爆炸并最大限度地减少长期预测的性能衰减。结合新的内存读取机制,XMem 在长视频数据集上的性能大大超过了最先进的性能,同时在短视频上与最先进的方法(不适用于长视频)相当数据集。
最新论文整理
ECCV2022
Updated on : 19 Jul 2022
total number : 37
Rethinking Data Augmentation for Robust Visual Question Answering
论文/Paper: http://arxiv.org/pdf/2207.08739
代码/Code: https://github.com/ItemZheng/KDDAug
Semantic Novelty Detection via Relational Reasoning
论文/Paper: http://arxiv.org/pdf/2207.08699
代码/Code: None
Label2Label: A Language Modeling Framework for Multi-Attribute Learning
论文/Paper: http://arxiv.org/pdf/2207.08677
代码/Code: https://github.com/Li-Wanhua/Label2Label
Action-based Contrastive Learning for Trajectory Prediction
论文/Paper: http://arxiv.org/pdf/2207.08664
代码/Code: None
Towards High-Fidelity Single-view Holistic Reconstruction of Indoor Scenes
论文/Paper: http://arxiv.org/pdf/2207.08656
代码/Code: https://github.com/UncleMEDM/InstPIFu
FakeCLR: Exploring Contrastive Learning for Solving Latent Discontinuity in Data-Efficient GANs
论文/Paper: http://arxiv.org/pdf/2207.08630
代码/Code: https://github.com/iceli1007/FakeCLR.
Class-incremental Novel Class Discovery
论文/Paper: http://arxiv.org/pdf/2207.08605
代码/Code: https://github.com/OatmealLiu/class-iNCD
Dense Cross-Query-and-Support Attention Weighted Mask Aggregation for Few-Shot Segmentation
论文/Paper: http://arxiv.org/pdf/2207.08549
代码/Code: None
DID-M3D: Decoupling Instance Depth for Monocular 3D Object Detection
论文/Paper: http://arxiv.org/pdf/2207.08531
代码/Code: https://github.com/SPengLiang/DID-M3D.
Hierarchical Feature Alignment Network for Unsupervised Video Object Segmentation
论文/Paper: http://arxiv.org/pdf/2207.08485
代码/Code: https://github.com/NUST-Machine-Intelligence-Laboratory/HFAN
Open-world Semantic Segmentation via Contrasting and Clustering Vision-Language Embedding
论文/Paper: http://arxiv.org/pdf/2207.08455
代码/Code: None
TokenMix: Rethinking Image Mixing for Data Augmentation in Vision Transformers
论文/Paper: http://arxiv.org/pdf/2207.08409
代码/Code: https://github.com/Sense-X/TokenMix
MPIB: An MPI-Based Bokeh Rendering Framework for Realistic Partial Occlusion Effects
论文/Paper: http://arxiv.org/pdf/2207.08403
代码/Code: None
Adversarial Contrastive Learning via Asymmetric InfoNCE
论文/Paper: http://arxiv.org/pdf/2207.08374
代码/Code: https://github.com/yqy2001/A-InfoNCE
SepLUT: Separable Image-adaptive Lookup Tables for Real-time Image Enhancement
论文/Paper: http://arxiv.org/pdf/2207.08351
代码/Code: None
Learning with Recoverable Forgetting
论文/Paper: http://arxiv.org/pdf/2207.08224
代码/Code: None
Fast-MoCo: Boost Momentum-based Contrastive Learning with Combinatorial Patches
论文/Paper: http://arxiv.org/pdf/2207.08220
代码/Code: None
Zero-Shot Temporal Action Detection via Vision-Language Prompting
论文/Paper: http://arxiv.org/pdf/2207.08184
代码/Code: https://github.com/sauradip/STALE
Watermark Vaccine: Adversarial Attacks to Prevent Watermark Removal
论文/Paper: http://arxiv.org/pdf/2207.08178
代码/Code: None
FashionViL: Fashion-Focused Vision-and-Language Representation Learning
论文/Paper: http://arxiv.org/pdf/2207.08150
代码/Code: https://github.com/BrandonHanx/mmf.
E-NeRV: Expedite Neural Video Representation with Disentangled Spatial-Temporal Context
论文/Paper: http://arxiv.org/pdf/2207.08132
代码/Code: https://github.com/kyleleey/E-NeRV.
CATRE: Iterative Point Clouds Alignment for Category-level Object Pose Refinement
论文/Paper: http://arxiv.org/pdf/2207.08082
代码/Code: None
Neural Color Operators for Sequential Image Retouching
论文/Paper: http://arxiv.org/pdf/2207.08080
代码/Code: https://github.com/amberwangyili/neurop
Semi-Supervised Keypoint Detector and Descriptor for Retinal Image Matching
论文/Paper: http://arxiv.org/pdf/2207.07932
代码/Code: None
Learning Quality-aware Dynamic Memory for Video Object Segmentation
论文/Paper: http://arxiv.org/pdf/2207.07922
代码/Code: https://github.com/workforai/QDMN.
SPSN: Superpixel Prototype Sampling Network for RGB-D Salient Object Detection
论文/Paper: http://arxiv.org/pdf/2207.07898
代码/Code: https://github.com/Hydragon516/SPSN
JPerceiver: Joint Perception Network for Depth, Pose and Layout Estimation in Driving Scenes
论文/Paper: http://arxiv.org/pdf/2207.07895
代码/Code: at~\href{https://github.com/sunnyHelen/JPerceiver}{https://github.com/sunnyHelen/JPerceiver}.
You Should Look at All Objects
论文/Paper: http://arxiv.org/pdf/2207.07889
代码/Code: None
NeFSAC: Neurally Filtered Minimal Samples
论文/Paper: http://arxiv.org/pdf/2207.07872
代码/Code: https://github.com/cavalli1234/NeFSAC.
CLOSE: Curriculum Learning On the Sharing Extent Towards Better One-shot NAS
论文/Paper: http://arxiv.org/pdf/2207.07868
代码/Code: https://github.com/walkerning/aw_nas.
TS2-Net: Token Shift and Selection Transformer for Text-Video Retrieval
论文/Paper: http://arxiv.org/pdf/2207.07852
代码/Code: None
Cross-Domain Cross-Set Few-Shot Learning via Learning Compact and Aligned Representations
论文/Paper: http://arxiv.org/pdf/2207.07826
代码/Code: https://github.com/WentaoChen0813/CDCS-FSL
Bagging Regional Classification Activation Maps for Weakly Supervised Object Localization
论文/Paper: http://arxiv.org/pdf/2207.07818
代码/Code: https://github.com/zh460045050/BagCAMs.
Self-calibrating Photometric Stereo by Neural Inverse Rendering
论文/Paper: http://arxiv.org/pdf/2207.07815
代码/Code: https://github.com/junxuan-li/SCPS-NIR
Learning Long-Term Spatial-Temporal Graphs for Active Speaker Detection
论文/Paper: http://arxiv.org/pdf/2207.07783
代码/Code: https://github.com/SRA2/SPELL
Towards Understanding The Semidefinite Relaxations of Truncated Least-Squares in Robust Rotation Search
论文/Paper: http://arxiv.org/pdf/2207.08350
代码/Code: None
TransGrasp: Grasp Pose Estimation of a Category of Objects by Transferring Grasps from Only One Labeled Instance
论文/Paper: http://arxiv.org/pdf/2207.07861
代码/Code: https://github.com/yanjh97/TransGrasp.
