6 papers
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…
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…
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…
Mixture-of-Top-k Attention: Efficient Attention via Scalable Fast Weights
Qishuai Wen, Zhiyuan Huang, Xianghan Meng +2
The vanilla self-attention mechanism in Transformers can be viewed as a two-layer fast-weight MLP, whose weights are dynamically induced by inputs and whose hidden dimension is equ…
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…
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…