11 citations · 20 across the 15 of their papers we have counts for
16 papers
Recovering Parametric Scenes from Very Few Time-of-Flight Pixels
Carter Sifferman, Yiquan Li, Yiming Li +4
We aim to recover the geometry of 3D parametric scenes using very few depth measurements from low-cost, commercially available time-of-flight sensors. These sensors offer very low…
TimeLoc: A Unified End-to-End Framework for Precise Timestamp Localization in Long Videos
Chen-Lin Zhang, Lin Sui, Shuming Liu +3
Temporal localization in untrimmed videos, which aims to identify specific timestamps, is crucial for video understanding but remains challenging. This task encompasses several sub…
Political-LLM: Large Language Models in Political Science
Lincan Li, Jiaqi Li, Catherine Chen +44
In recent years, large language models (LLMs) have been widely adopted in political science tasks such as election prediction, sentiment analysis, policy impact assessment, and mis…
Harnessing Temporal Causality for Advanced Temporal Action Detection
Shuming Liu, Lin Sui, Chen-Lin Zhang +3
As a fundamental task in long-form video understanding, temporal action detection (TAD) aims to capture inherent temporal relations in untrimmed videos and identify candidate actio…
Ctrl-X: Controlling Structure and Appearance for Text-To-Image Generation Without Guidance
Kuan Heng Lin, Sicheng Mo, Ben Klingher +2
Recent controllable generation approaches such as FreeControl and Diffusion Self-Guidance bring fine-grained spatial and appearance control to text-to-image (T2I) diffusion models…
SnAG: Scalable and Accurate Video Grounding
Fangzhou Mu, Sicheng Mo, Yin Li
Temporal grounding of text descriptions in videos is a central problem in vision-language learning and video understanding. Existing methods often prioritize accuracy over scalabil…