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cs.CV2026

Learning Deep Modality-Shared Self-Expressiveness for Image Clustering with Textual Information

Xianghan Meng, Wei He, Zhiyuan Huang +1

Leveraging textual information for image clustering has emerged as a promising direction, largely owing to the powerful representations learned by Vision-Language Models (VLMs). Ex…

cs.CV2026

Jointly Learning Structured Representations and Stabilized Affinity for Human Motion Segmentation

Xianghan Meng, Zhiyuan Huang, Zhengyu Tong +1

Human Motion Segmentation (HMS), which aims to partition a video into non-overlapping segments corresponding to different human motions, has recently attracted increasing research…

cs.CV2026

Multi-Modal Representation Learning via Semi-Supervised Rate Reduction for Generalized Category Discovery

Wei He, Xianghan Meng, Zhiyuan Huang +3

Generalized Category Discovery (GCD) aims to identify both known and unknown categories, with only partial labels given for the known categories, posing a challenging open-set reco…

cs.CV2025

Temporal Rate Reduction Clustering for Human Motion Segmentation

Xianghan Meng, Zhengyu Tong, Zhiyuan Huang +1

Human Motion Segmentation (HMS), which aims to partition videos into non-overlapping human motions, has attracted increasing research attention recently. Existing approaches for HM…

cs.CV2025

Exploring a Principled Framework for Deep Subspace Clustering

Xianghan Meng, Zhiyuan Huang, Wei He +3

Subspace clustering is a classical unsupervised learning task, built on a basic assumption that high-dimensional data can be approximated by a union of subspaces (UoS). Nevertheles…