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工业质检领域相关近期顶会论文汇总CVPR2025

目录

    • 异常检测Anomaly Detection
      • 多类别
      • 数据集
      • 开集有监督异常检测Open-set Supervised Anomaly Detection(OSAD)
      • 基于多模态大模型能力
    • 骨干网络
      • Mamba系列(mamba为transformer后的新骨干网络形式)
      • 其他
    • 目标检测
      • 开集识别
      • DETR
      • 实例检测Instance Detection
    • 分割
    • 异常生成
    • 图像编辑
    • few-shot
      • 视觉语言模型VLM
      • 迁移学习
    • zero-shot
      • 多模态大模型MLLM
    • 其他
      • 主动学习
      • 半监督semi-supervised
      • 增量学习

异常检测Anomaly Detection

  • ⭐️UniNet: A Contrastive Learning-guided Unified Framework with Feature Selection for Anomaly Detection, Code,MVTech当前排名第2
  • ⭐️AA-CLIP: Enhancing Zero-shot Anomaly Detection via Anomaly-Aware CLIP, Code
  • Correcting Deviations from Normality: A Reformulated Diffusion Model for Multi-Class Unsupervised Anomaly Detection, Code
  • star:TailedCore : Few-Shot Sampling for Unsupervised Long-Tail Noisy Anomaly Detection, Code
  • Odd-One-Out: Anomaly Detection by Comparing with Neighbors, Code

多类别

  • One-for-More: Continual Diffusion Model for Anomaly Detection, Code,一个模型多类别异常检测
  • AnomalyNCD: Towards Novel Anomaly Class Discovery in Industrial Scenarios, Code
  • Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection, Code

数据集

  • MANTA: A Large-Scale Multi-View and Visual-Text Anomaly Detection Dataset for Tiny Objects, Dataset

开集有监督异常检测Open-set Supervised Anomaly Detection(OSAD)

  • Distribution Prototype Diffusion Learning for Open-set Supervised Anomaly Detection

基于多模态大模型能力

  • Towards Training-free Anomaly Detection with Vision and Language Foundation Models, Code

骨干网络

Mamba系列(mamba为transformer后的新骨干网络形式)

  • MambaVision: A Hybrid Mamba-Transformer Vision Backbone,Code
  • MobileMamba: Lightweight Multi-Receptive Visual Mamba Network, Code

其他

  • Transformers without Normalization, Code,不用normalization也能取得相同的效果?
  • ⭐️ShiftwiseConv: Small Convolutional Kernel with Large Kernel Effect, Code,近期的大卷积核带来了超越transformer的效果,why?
  • OverLoCK: An Overview-first-Look-Closely-next ConvNet with Context-Mixing Dynamic Kernels, Code,自上而下的注意力+动态卷积

目标检测

开集识别

  • LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models, Code
  • SGC-Net: Stratified Granular Comparison Network for Open-Vocabulary HOI Detection, Code

DETR

  • DEIM: DETR with Improved Matching for Fast Convergence, Code, 加速DETR类目标检测的训练和推理速度,训练速度减少50%!🙀

实例检测Instance Detection

  • Solving Instance Detection from an Open-World Perspective, Code

分割

  • Mask-Adapter: The Devil is in the Masks for Open-Vocabulary Segmentation,Code
  • ROS-SAM: High-Quality Interactive Segmentation for Remote Sensing Moving Object, Code

异常生成

  • Anomaly Anything: Promptable Unseen Visual Anomaly Generation
  • Dual-Interrelated Diffusion Model for Few-Shot Anomaly Image Generation

图像编辑

  • Edit Away and My Face Will not Stay: Personal Biometric Defense against Malicious Generative Editing, Code
  • h-Edit: Effective and Flexible Diffusion-Based Editing via Doob’s h-Transform, Code
  • Preserve or Modify? Context-Aware Evaluation for Balancing Preservation and Modification in Text-Guided Image Editing, Code

few-shot

视觉语言模型VLM

  • Rethinking Few-Shot Adaptation of Vision-Language Models in Two Stages, Code
  • UniVAD: A Training-free Unified Model for Few-shot Visual Anomaly Detection, Code

迁移学习

  • MMRL: Multi-Modal Representation Learning for Vision-Language Models, Code

zero-shot

多模态大模型MLLM

  • Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models, Code
  • Bayesian Prompt Flow Learning for Zero-Shot Anomaly Detection, Code

其他

主动学习

  • Rethinking Epistemic and Aleatoric Uncertainty for Active Open-Set Annotation: An Energy-Based Approach, Code,开集主动学习

半监督semi-supervised

  • Unlocking the Potential of Unlabeled Data in Semi-Supervised Domain Generalization, Code

增量学习

  • Dual Consolidation for Pre - Trained Model - Based Domain - Incremental Learning, Code

参考:

  1. https://cvpr.thecvf.com/Conferences/2025/AcceptedPapers
  2. https://zhuanlan.zhihu.com/p/30204993641
  3. https://github.com/amusi/CVPR2025-Papers-with-Code?tab=readme-ov-file
  4. https://github.com/Paper2Chinese/CVPR-2025-reading-papers-with-code?tab=readme-ov-file
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