most citedReasoning Segmentation for Images and Videos: A Survey

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV20251 cited

Reasoning Segmentation for Images and Videos: A Survey

Yiqing Shen, Chenjia Li, Fei Xiong +4

Reasoning Segmentation (RS) aims to delineate objects based on implicit text queries, the interpretation of which requires reasoning and knowledge integration. Unlike the tradition…

cs.CV2025

RVTBench: A Benchmark for Visual Reasoning Tasks

Yiqing Shen, Chenjia Li, Chenxiao Fan +1

Visual reasoning, the capability to interpret visual input in response to implicit text query through multi-step reasoning, remains a challenge for deep learning models due to the…