219 citations · 302 across the 16 of their papers we have counts for
8 papers · 1 filter
Exploring Stochastic Autoregressive Image Modeling for Visual Representation
Yu Qi, Fan Yang, Yousong Zhu +4
Autoregressive language modeling (ALM) have been successfully used in self-supervised pre-training in Natural language processing (NLP). However, this paradigm has not achieved com…
MIAD: A Maintenance Inspection Dataset for Unsupervised Anomaly Detection
Tianpeng Bao, Jiadong Chen, Wei Li +5
Visual anomaly detection plays a crucial role in not only manufacturing inspection to find defects of products during manufacturing processes, but also maintenance inspection to ke…
Obj2Seq: Formatting Objects as Sequences with Class Prompt for Visual Tasks
Zhiyang Chen, Yousong Zhu, Zhaowen Li +8
Visual tasks vary a lot in their output formats and concerned contents, therefore it is hard to process them with an identical structure. One main obstacle lies in the high-dimensi…
Learning from Future: A Novel Self-Training Framework for Semantic Segmentation
Ye Du, Yujun Shen, Haochen Wang +6
Self-training has shown great potential in semi-supervised learning. Its core idea is to use the model learned on labeled data to generate pseudo-labels for unlabeled samples, and…
Positive-Negative Equal Contrastive Loss for Semantic Segmentation
Jing Wang, Jiangyun Li, Wei Li +3
The contextual information is critical for various computer vision tasks, previous works commonly design plug-and-play modules and structural losses to effectively extract and aggr…
Benchmarking Unsupervised Anomaly Detection and Localization
Ye Zheng, Xiang Wang, Yu Qi +2
Unsupervised anomaly detection and localization, as of one the most practical and challenging problems in computer vision, has received great attention in recent years. From the ti…