activity
20242026
collaborators

6 papers

cs.CV2026

CS-CLIP: Compositional Scene Graph-guided CLIP for Robust Compositional Reasoning

SeongJun Jeong, Minjoon Jung, Woo Suk Choi +2

Vision-language models (VLMs) demonstrate strong performance across compositional reasoning benchmarks, which require reasoning over semantic perturbations of objects, attributes,…

cs.CV2026

EvoGround: Self-Evolving Video Agents for Video Temporal Grounding

Minjoon Jung, Byoung-Tak Zhang, Lorenzo Torresani

Video temporal grounding (VTG) takes an untrimmed video and a natural-language query as input and localizes the temporal moment that best matches the query. Existing methods rely o…

cs.CV2026

Kinematics-Driven Gaussian Shape Deformation for Blurry Monocular Dynamic Scenes

Yeon-Ji Song, Kiyoung Kwon, Junoh Lee +2

Reconstructing dynamic 3D scenes from blurry monocular videos is challenging as motion-induced blur entangles object motion and geometry, hindering geometric consistency. We presen…

cs.CV2025

EgoExo-Con: Exploring View-Invariant Video Temporal Understanding

Minjoon Jung, Junbin Xiao, Junghyun Kim +2

Do Video-LLMs have consistent temporal understanding when videos capture the same event from different viewpoints? To study this question, we introduce EgoExo-Con(sistency), a benc…

cs.CV2025

Exploring Ordinal Bias in Action Recognition for Instructional Videos

Joochan Kim, Minjoon Jung, Byoung-Tak Zhang

Action recognition models have achieved promising results in understanding instructional videos. However, they often rely on dominant, dataset-specific action sequences rather than…

cs.CV2024

On the Consistency of Video Large Language Models in Temporal Comprehension

Minjoon Jung, Junbin Xiao, Byoung-Tak Zhang +1

Video large language models (Video-LLMs) can temporally ground language queries and retrieve video moments. Yet, such temporal comprehension capabilities are neither well-studied n…