1 citations · 3 across the 10 of their papers we have counts for
13 papers
Counterfactual World Models via Digital Twin-conditioned Video Diffusion
Yiqing Shen, Aiza Maksutova, Chenjia Li +1
World models learn to predict the temporal evolution of visual observations given a control signal, potentially enabling agents to reason about environments through forward simulat…
Text-Driven Reasoning Video Editing via Reinforcement Learning on Digital Twin Representations
Yiqing Shen, Chenjia Li, Mathias Unberath
Text-driven video editing enables users to modify video content only using text queries. While existing methods can modify video content if explicit descriptions of editing targets…
Reasoning Text-to-Video Retrieval via Digital Twin Video Representations and Large Language Models
Yiqing Shen, Chenxiao Fan, Chenjia Li +1
The goal of text-to-video retrieval is to search large databases for relevant videos based on text queries. Existing methods have progressed to handling explicit queries where the…
Fast Reasoning Segmentation for Images and Videos
Yiqing Shen, Mathias Unberath
Reasoning segmentation enables open-set object segmentation via implicit text queries, therefore serving as a foundation for embodied agents that should operate autonomously in rea…
Constructing and Interpreting Digital Twin Representations for Visual Reasoning via Reinforcement Learning
Yiqing Shen, Mathias Unberath
Visual reasoning may require models to interpret images and videos and respond to implicit text queries across diverse output formats, from pixel-level segmentation masks to natura…
Temporally-Constrained Video Reasoning Segmentation and Automated Benchmark Construction
Yiqing Shen, Chenjia Li, Chenxiao Fan +1
Conventional approaches to video segmentation are confined to predefined object categories and cannot identify out-of-vocabulary objects, let alone objects that are not identified…