ECCV2022 &CVPR2022论文速递2022.7.21!& demo

2022-12-11 11:20:08 浏览数 (1)

整理:AI算法与图像处理

CVPR2022论文和代码整理:https://github.com/DWCTOD/CVPR2022-Papers-with-Code-Demo

ECCV2022论文和代码整理:https://github.com/DWCTOD/ECCV2022-Papers-with-Code-Demo

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 : 21 Jul 2022
total number : 43

Discover and Mitigate Unknown Biases with Debiasing Alternate Networks

  • 论文/Paper: http://arxiv.org/pdf/2207.10077
  • 代码/Code: https://github.com/zhihengli-UR/DebiAN

Monocular 3D Object Reconstruction with GAN Inversion

  • 论文/Paper: http://arxiv.org/pdf/2207.10061
  • 代码/Code: https://github.com/junzhezhang/mesh-inversion

3D Clothed Human Reconstruction in the Wild

  • 论文/Paper: http://arxiv.org/pdf/2207.10053
  • 代码/Code: https://github.com/hygenie1228/clothwild_release

Densely Constrained Depth Estimator for Monocular 3D Object Detection

  • 论文/Paper: http://arxiv.org/pdf/2207.10047
  • 代码/Code: https://github.com/bravegroup/dcd

MOTCOM: The Multi-Object Tracking Dataset Complexity Metric

  • 论文/Paper: http://arxiv.org/pdf/2207.10031
  • 代码/Code: None

Difficulty-Aware Simulator for Open Set Recognition

  • 论文/Paper: http://arxiv.org/pdf/2207.10024
  • 代码/Code: https://github.com/wjun0830/difficulty-aware-simulator

Tailoring Self-Supervision for Supervised Learning

  • 论文/Paper: http://arxiv.org/pdf/2207.10023
  • 代码/Code: https://github.com/wjun0830/localizable-rotation

Generative Domain Adaptation for Face Anti-Spoofing

  • 论文/Paper: http://arxiv.org/pdf/2207.10015
  • 代码/Code: None

Overcoming Shortcut Learning in a Target Domain by Generalizing Basic Visual Factors from a Source Domain

  • 论文/Paper: http://arxiv.org/pdf/2207.10002
  • 代码/Code: https://github.com/boschresearch/sourcegen

DecoupleNet: Decoupled Network for Domain Adaptive Semantic Segmentation

  • 论文/Paper: http://arxiv.org/pdf/2207.09988
  • 代码/Code: https://github.com/dvlab-research/decouplenet

Temporal and cross-modal attention for audio-visual zero-shot learning

  • 论文/Paper: http://arxiv.org/pdf/2207.09966
  • 代码/Code: https://github.com/explainableml/tcaf-gzsl

Telepresence Video Quality Assessment

  • 论文/Paper: http://arxiv.org/pdf/2207.09956
  • 代码/Code: None

Learning Pedestrian Group Representations for Multi-modal Trajectory Prediction

  • 论文/Paper: http://arxiv.org/pdf/2207.09953
  • 代码/Code: https://github.com/inhwanbae/gpgraph

Towards Efficient and Scale-Robust Ultra-High-Definition Image Demoireing

  • 论文/Paper: http://arxiv.org/pdf/2207.09935
  • 代码/Code: None

Robust Landmark-based Stent Tracking in X-ray Fluoroscopy

  • 论文/Paper: http://arxiv.org/pdf/2207.09933
  • 代码/Code: None

Negative Samples are at Large: Leveraging Hard-distance Elastic Loss for Re-identification

  • 论文/Paper: http://arxiv.org/pdf/2207.09884
  • 代码/Code: None

Discrete-Constrained Regression for Local Counting Models

  • 论文/Paper: http://arxiv.org/pdf/2207.09865
  • 代码/Code: None

UNIF: United Neural Implicit Functions for Clothed Human Reconstruction and Animation

  • 论文/Paper: http://arxiv.org/pdf/2207.09835
  • 代码/Code: https://github.com/ShenhanQian/UNIF

CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentation

  • 论文/Paper: http://arxiv.org/pdf/2207.09778
  • 代码/Code: https://github.com/saltoricristiano/cosmix-uda

Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action Recognition

  • 论文/Paper: http://arxiv.org/pdf/2207.09767
  • 代码/Code: https://github.com/canbaoburen/CoDT

GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation

  • 论文/Paper: http://arxiv.org/pdf/2207.09763
  • 代码/Code: https://github.com/saltoricristiano/gipso-sfouda

Feature Representation Learning for Unsupervised Cross-domain Image Retrieval

  • 论文/Paper: http://arxiv.org/pdf/2207.09721
  • 代码/Code: https://github.com/conghuihu/ucdir

Resolving Copycat Problems in Visual Imitation Learning via Residual Action Prediction

  • 论文/Paper: http://arxiv.org/pdf/2207.09705
  • 代码/Code: None

Robust Object Detection With Inaccurate Bounding Boxes

  • 论文/Paper: http://arxiv.org/pdf/2207.09697
  • 代码/Code: https://github.com/cxliu0/OA-MIL.

Efficient Meta-Tuning for Content-aware Neural Video Delivery

  • 论文/Paper: http://arxiv.org/pdf/2207.09691
  • 代码/Code: https://github.com/neural-video-delivery/emt-pytorch-eccv2022

Object-Compositional Neural Implicit Surfaces

  • 论文/Paper: http://arxiv.org/pdf/2207.09686
  • 代码/Code: https://github.com/qianyiwu/objsdf

Explaining Deepfake Detection by Analysing Image Matching

  • 论文/Paper: http://arxiv.org/pdf/2207.09679
  • 代码/Code: https://github.com/megvii-research/fst-matching

ERA: Expert Retrieval and Assembly for Early Action Prediction

  • 论文/Paper: http://arxiv.org/pdf/2207.09675
  • 代码/Code: None

GRIT: Faster and Better Image captioning Transformer Using Dual Visual Features

  • 论文/Paper: http://arxiv.org/pdf/2207.09666
  • 代码/Code: https://github.com/davidnvq/grit

Streamable Neural Fields

  • 论文/Paper: http://arxiv.org/pdf/2207.09663
  • 代码/Code: https://github.com/jwcho5576/streamable_nf

Unsupervised Domain Adaptation for One-stage Object Detector using Offsets to Bounding Box

  • 论文/Paper: http://arxiv.org/pdf/2207.09656
  • 代码/Code: None

Learning Topological Interactions for Multi-Class Medical Image Segmentation

  • 论文/Paper: http://arxiv.org/pdf/2207.09654
  • 代码/Code: https://github.com/topoxlab/topointeraction

Aware of the History: Trajectory Forecasting with the Local Behavior Data

  • 论文/Paper: http://arxiv.org/pdf/2207.09646
  • 代码/Code: None

Hierarchically Self-Supervised Transformer for Human Skeleton Representation Learning

  • 论文/Paper: http://arxiv.org/pdf/2207.09644
  • 代码/Code: None

Perspective Phase Angle Model for Polarimetric 3D Reconstruction

  • 论文/Paper: http://arxiv.org/pdf/2207.09629
  • 代码/Code: https://github.com/gcchen97/ppa4p3d

Explicit Image Caption Editing

  • 论文/Paper: http://arxiv.org/pdf/2207.09625
  • 代码/Code: https://github.com/baaaad/ece

Unsupervised Deep Multi-Shape Matching

  • 论文/Paper: http://arxiv.org/pdf/2207.09610
  • 代码/Code: None

AiATrack: Attention in Attention for Transformer Visual Tracking

  • 论文/Paper: http://arxiv.org/pdf/2207.09603
  • 代码/Code: https://github.com/Little-Podi/AiATrack

Tip-Adapter: Training-free Adaption of CLIP for Few-shot Classification

  • 论文/Paper: http://arxiv.org/pdf/2207.09519
  • 代码/Code: https://github.com/gaopengcuhk/tip-adapter

Contributions of Shape, Texture, and Color in Visual Recognition

  • 论文/Paper: http://arxiv.org/pdf/2207.09510
  • 代码/Code: https://github.com/gyhandy/humanoid-vision-engine

An Efficient Method for Face Quality Assessment on the Edge

  • 论文/Paper: http://arxiv.org/pdf/2207.09505
  • 代码/Code: None

Invariant Feature Learning for Generalized Long-Tailed Classification

  • 论文/Paper: http://arxiv.org/pdf/2207.09504
  • 代码/Code: https://github.com/kaihuatang/generalized-long-tailed-benchmarks.pytorch

Single Frame Atmospheric Turbulence Mitigation: A Benchmark Study and A New Physics-Inspired Transformer Model

  • 论文/Paper: http://arxiv.org/pdf/2207.10040
  • 代码/Code: None

CVPR2022

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