6 papers · 1 filter
Identifying Latent Concepts and Structures for Generalized Category Discovery
Boyang Dai, Chaoqi Chen, Yizhou Yu
Generalized Category Discovery (GCD) aims to recognize known classes while autonomously discovering novel ones in open-world settings. However, current approaches primarily focus o…
Mitigating Simplicity Bias in OOD Detection through Object Co-occurrence Analysis
Boyang Dai, Chaoqi Chen, Yizhou Yu
Out-of-distribution (OOD) detection is crucial for ensuring the reliability of deep learning models. Existing methods mostly focus on regular entangled representations to discrimin…
Back to Source: Open-Set Continual Test-Time Adaptation via Domain Compensation
Yingkai Yang, Chaoqi Chen, Hui Huang
Test-Time Adaptation (TTA) aims to mitigate distributional shifts between training and test domains during inference time. However, existing TTA methods fall short in the realistic…
LaMamba-Diff: Linear-Time High-Fidelity Diffusion Models Based on Local Attention and Mamba
Yunxiang Fu, Chaoqi Chen, Yizhou Yu
Recent Transformer-based diffusion models have shown remarkable performance, largely attributed to the ability of the self-attention mechanism to accurately capture both global and…
Bootstrap Segmentation Foundation Model under Distribution Shift via Object-Centric Learning
Luyao Tang, Yuxuan Yuan, Chaoqi Chen +3
Foundation models have made incredible strides in achieving zero-shot or few-shot generalization, leveraging prompt engineering to mimic the problem-solving approach of human intel…
A Survey on Graph Neural Networks and Graph Transformers in Computer Vision: A Task-Oriented Perspective
Chaoqi Chen, Yushuang Wu, Qiyuan Dai +5
Graph Neural Networks (GNNs) have gained momentum in graph representation learning and boosted the state of the art in a variety of areas, such as data mining (\emph{e.g.,} social…