6 papers
Trust-Aware Joint Feature-Prediction Discrepancy for Robust Domain Adaptation
Xi Ding, Lei Wang, Syuan-Hao Li +1
Domain adaptation aims to mitigate performance degradation caused by distribution shifts between a labeled source domain and an unlabeled or sparsely labeled target domain. Most ex…
Subspace Kernel Learning on Tensor Sequences
Lei Wang, Xi Ding, Yongsheng Gao +1
Learning from structured multi-way data, represented as higher-order tensors, requires capturing complex interactions across tensor modes while remaining computationally efficient.…
Learning Time in Static Classifiers
Xi Ding, Lei Wang, Piotr Koniusz +1
Real-world visual data rarely presents as isolated, static instances. Instead, it often evolves gradually over time through variations in pose, lighting, object state, or scene con…
Graph Your Own Prompt
Xi Ding, Lei Wang, Piotr Koniusz +1
We propose Graph Consistency Regularization (GCR), a novel framework that injects relational graph structures, derived from model predictions, into the learning process to promote…
Do Language Models Understand Time?
Xi Ding, Lei Wang
Large language models (LLMs) have revolutionized video-based computer vision applications, including action recognition, anomaly detection, and video summarization. Videos inherent…
Quo Vadis, Anomaly Detection? LLMs and VLMs in the Spotlight
Xi Ding, Lei Wang
Video anomaly detection (VAD) has witnessed significant advancements through the integration of large language models (LLMs) and vision-language models (VLMs), addressing critical…