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cs.CV2026

Why Far Looks Up: Probing Spatial Representation in Vision-Language Models

Cheolhong Min, Jaeyun Jung, Daeun Lee +5

Vision-language models (VLMs) achieve strong performance on spatial reasoning benchmarks, yet it remains unclear whether this reflects structured 3D understanding or reliance on st…

cs.CV2026

StreamGaze: Gaze-Guided Temporal Reasoning and Proactive Understanding in Streaming Videos

Daeun Lee, Subhojyoti Mukherjee, Branislav Kveton +6

Streaming video understanding requires models not only to process temporally incoming frames, but also to anticipate user intention for realistic applications such as Augmented Rea…

cs.CV2026

Self-Correcting Text-to-Video Generation with Misalignment Detection and Localized Refinement

Daeun Lee, Jaehong Yoon, Jaemin Cho +1

Recent text-to-video (T2V) diffusion models have made remarkable progress in generating high-quality videos. However, they often struggle to align with complex text prompts, partic…

cs.CV2026

VisionCoach: Reinforcing Grounded Video Reasoning via Visual-Perception Prompting

Daeun Lee, Shoubin Yu, Yue Zhang +1

Video reasoning requires models to locate and track question-relevant evidence across frames. While reinforcement learning (RL) with verifiable rewards improves accuracy, it still…

cs.CV2025

Video-Skill-CoT: Skill-based Chain-of-Thoughts for Domain-Adaptive Video Reasoning

Daeun Lee, Jaehong Yoon, Jaemin Cho +1

Recent advances in Chain-of-Thought (CoT) reasoning have improved complex video understanding, but existing methods often struggle to adapt to domain-specific skills (e.g., event d…

cs.CV2024

HD Maps are Lane Detection Generalizers: A Novel Generative Framework for Single-Source Domain Generalization

Daeun Lee, Minhyeok Heo, Jiwon Kim

Lane detection is a vital task for vehicles to navigate and localize their position on the road. To ensure reliable driving, lane detection models must have robust generalization p…