2 citations · 2 across the 5 of their papers we have counts for
5 papers · 1 filter
TT-VidT: Decoupling the Temporal Axis for Efficient Motion-Centric Video Pretraining
Shih-Ying Yeh, Daniel Z. Kaplan, Xuehai Wang +3
Comparisons in video self-supervised learning often evaluate complete training recipes rather than isolating the method itself: architecture, objective, data exposure, schedule, sc…
ReactVAU: A Slow-Fast Decoupled Framework for Streaming Video Anomaly Understanding
Chia-Hui Chen, Shih-Ying Yeh, Fu-En Yang +2
In this paper, we propose ReactVAU, a Slow-Fast Decoupled Framework for real-time streaming Video Anomaly Understanding (VAU). Existing VAU methods rely on offline inference with g…
Home-made Diffusion Model from Scratch to Hatch
Shih-Ying Yeh
We introduce Home-made Diffusion Model (HDM), an efficient yet powerful text-to-image diffusion model optimized for training (and inferring) on consumer-grade hardware. HDM achieve…
TIPO: Text to Image with Text Presampling for Prompt Optimization
Shih-Ying Yeh, Yi Li, Sang-Hyun Park +5
TIPO (Text-to-Image Prompt Optimization) introduces an efficient approach for automatic prompt refinement in text-to-image (T2I) generation. Starting from simple user prompts, TIPO…
Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions
Yu-Guan Hsieh, Cheng-Yu Hsieh, Shih-Ying Yeh +7
Humans describe complex scenes with compositionality, using simple text descriptions enriched with links and relationships. While vision-language research has aimed to develop mode…