4 papers
Time-JEPA: Grounding Video World Models with Physical Time Series
Shenyi Li, Ziyang Zhang, Wen Wu +2
Video world models learn how visual environments evolve by predicting missing or future content. However, physical-state information can provide useful context for predicting how e…
MMTA: Benchmarking Multimodal Temporal Analysis with Time Series, Text, and Vision
Ziyang Zhang, Shenyi Li, Yilin Wang +4
Time-series analysis is increasingly studied in multimodal settings, yet most benchmarks pair temporal signals with text or with visualizations derived from the same signal. This l…
Learning Depth from Past Selves: Self-Evolution Contrast for Robust Depth Estimation
Jing Cao, Kui Jiang, Shenyi Li +2
Self-supervised depth estimation has gained significant attention in autonomous driving and robotics. However, existing methods exhibit substantial performance degradation under ad…
NTIRE 2025 Challenge on HR Depth from Images of Specular and Transparent Surfaces
Pierluigi Zama Ramirez, Fabio Tosi, Luigi Di Stefano +36
This paper reports on the NTIRE 2025 challenge on HR Depth From images of Specular and Transparent surfaces, held in conjunction with the New Trends in Image Restoration and Enhanc…