activity
20242026
collaborators

9 papers

cs.CL2026

CHE-TKG: Collaborative Historical Evidence and Evolutionary Dynamics Learning for Temporal Knowledge Graph Reasoning

Shuai-long Lei, Xiaobin Zhu, Jiarui Liang +3

Temporal knowledge graph (TKG) reasoning aims to predict future events from historical facts. A key challenge lies in jointly capturing two sources of predictive information in TKG…

cs.AI2026

CID-TKG: Collaborative Historical Invariance and Evolutionary Dynamics Learning for Temporal Knowledge Graph Reasoning

Shuai-Long Lei, Xiaobin Zhu, Jiarui Liang +3

Temporal knowledge graph (TKG) reasoning aims to infer future facts at unseen timestamps from temporally evolving entities and relations. Despite recent progress, existing approach…

cs.CV2025

DPFlow: Adaptive Optical Flow Estimation with a Dual-Pyramid Framework

Henrique Morimitsu, Xiaobin Zhu, Roberto M. Cesar +2

Optical flow estimation is essential for video processing tasks, such as restoration and action recognition. The quality of videos is constantly increasing, with current standards…

cs.CV2025

Unsupervised Real-World Super-Resolution via Rectified Flow Degradation Modelling

Hongyang Zhou, Xiaobin Zhu, Liuling Chen +4

Unsupervised real-world super-resolution (SR) faces critical challenges due to the complex, unknown degradation distributions in practical scenarios. Existing methods struggle to g…

cs.CV2025

Similarity Matters: A Novel Depth-guided Network for Image Restoration and A New Dataset

Junyi He, Liuling Chen, Hongyang Zhou +5

Image restoration has seen substantial progress in recent years. However, existing methods often neglect depth information, which hurts similarity matching, results in attention di…

cs.CV2025

VCapsBench: A Large-scale Fine-grained Benchmark for Video Caption Quality Evaluation

Shi-Xue Zhang, Hongfa Wang, Duojun Huang +3

Video captions play a crucial role in text-to-video generation tasks, as their quality directly influences the semantic coherence and visual fidelity of the generated videos. Altho…