CVPR 2024 论文和代码速递! 2024.3.20

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2024-04-11 18:21

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CVPR 2024

Updated on : 20 Mar 2024

total number : 10

TexTile: A Differentiable Metric for Texture Tileability

  • 论文/Paper: http://arxiv.org/pdf/2403.12961

  • 代码/Code: None

Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly Detection

  • 论文/Paper: http://arxiv.org/pdf/2403.12580

  • 代码/Code: None

Adapting Visual-Language Models for Generalizable Anomaly Detection in Medical Images

  • 论文/Paper: http://arxiv.org/pdf/2403.12570

  • 代码/Code: https://github.com/mediabrain-sjtu/mvfa-ad

ExACT: Language-guided Conceptual Reasoning and Uncertainty Estimation for Event-based Action Recognition and More

  • 论文/Paper: http://arxiv.org/pdf/2403.12534

  • 代码/Code: None

UniBind: LLM-Augmented Unified and Balanced Representation Space to Bind Them All

  • 论文/Paper: http://arxiv.org/pdf/2403.12532

  • 代码/Code: None

Semantics, Distortion, and Style Matter: Towards Source-free UDA for Panoramic Segmentation

  • 论文/Paper: http://arxiv.org/pdf/2403.12505

  • 代码/Code: None

Task-Customized Mixture of Adapters for General Image Fusion

  • 论文/Paper: http://arxiv.org/pdf/2403.12494

  • 代码/Code: https://github.com/YangSun22/TC-MoA

Privacy-Preserving Face Recognition Using Trainable Feature Subtraction

  • 论文/Paper: http://arxiv.org/pdf/2403.12457

  • 代码/Code: https://github.com/Tencent/TFace

DeCoTR: Enhancing Depth Completion with 2D and 3D Attentions

  • 论文/Paper: http://arxiv.org/pdf/2403.12202

  • 代码/Code: None

Improving Generalization via Meta-Learning on Hard Samples

  • 论文/Paper: http://arxiv.org/pdf/2403.12236

  • 代码/Code: None

ICLR 2024

Updated on : 20 Mar 2024

total number : 2

Non-negative Contrastive Learning

  • 论文/Paper: http://arxiv.org/pdf/2403.12459

  • 代码/Code: https://github.com/pku-ml/non_neg

Do Generated Data Always Help Contrastive Learning?

  • 论文/Paper: http://arxiv.org/pdf/2403.12448

  • 代码/Code: https://github.com/pku-ml/adainf

AAAI 2024

Updated on : 20 Mar 2024

total number : 2

Confusing Pair Correction Based on Category Prototype for Domain Adaptation under Noisy Environments

  • 论文/Paper: http://arxiv.org/pdf/2403.12883

  • 代码/Code: https://github.com/hehxcf/cpc

Fusing Domain-Specific Content from Large Language Models into Knowledge Graphs for Enhanced Zero Shot Object State Classification

  • 论文/Paper: http://arxiv.org/pdf/2403.12151

  • 代码/Code: None

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