10 papers · 1 filter
When Predicting Nothing Beats SAM 3: Revisiting Evaluation in Video Object Segmentation
Jihwan Hong, Woohyeon Park, Jaeik Kim +1
Video Object Segmentation (VOS) in complex and long videos is increasingly important for real-world applications, where target objects often appear only intermittently within long…
What Comes Next? Omni-StoryBench for Evaluating Story-Grounded Omnimodal Generation
Sieun Hyeon, Yejoon Lee, Mintaek Lim +3
Omnimodal evaluation should go beyond independent text, image, and speech production: individually plausible outputs may not express a coherent shared event. We introduce Omni-Stor…
MI-CXR: A Benchmark for Longitudinal Reasoning over Multi-Interval Chest X-rays
Sunghwan Steve Cho, Yunseok Han, Jaeyoung Do
Longitudinal chest X-ray (CXR) interpretation requires reasoning over disease evolution across multiple patient visits, yet most existing medical VQA benchmarks focus on single ima…
Report of the 5th PVUW Challenge: Towards More Diverse Modalities in Pixel-Level Understanding
Chang Liu, Henghui Ding, Nikhila Ravi +40
This report summarizes the objectives, datasets, and top-performing methodologies of the 2026 Pixel-level Video Understanding in the Wild (PVUW) Challenge, hosted at CVPR 2026, whi…
VIRST: Video-Instructed Reasoning Assistant for SpatioTemporal Segmentation
Jihwan Hong, Jaeyoung Do
Referring Video Object Segmentation (RVOS) aims to segment target objects in videos based on natural language descriptions. However, fixed keyframe-based approaches that couple a v…
3rd Place of MeViS-Audio Track of the 5th PVUW: VIRST-Audio
Jihwan Hong, Jaeyoung Do
Audio-based Referring Video Object Segmentation (ARVOS) requires grounding audio queries into pixel-level object masks over time, posing challenges in bridging acoustic signals wit…
MEDIC-AD: Towards Medical Vision-Language Model's Clinical Intelligence
Woohyeon Park, Jaeik Kim, Sunghwan Steve Cho +7
Lesion detection, symptom tracking, and visual explainability are central to real-world medical image analysis, yet current medical Vision-Language Models (VLMs) still lack mechani…
Exploring and Leveraging Class Vectors for Classifier Editing
Jaeik Kim, Jaeyoung Do
Image classifiers play a critical role in detecting diseases in medical imaging and identifying anomalies in manufacturing processes. However, their predefined behaviors after exte…
MMPB: It's Time for Multi-Modal Personalization
Jaeik Kim, Woojin Kim, Woohyeon Park +1
Visual personalization is essential in user-facing AI systems such as smart homes and healthcare, where aligning model behavior with user-centric concepts is critical. However, rec…
SECOND: Mitigating Perceptual Hallucination in Vision-Language Models via Selective and Contrastive Decoding
Woohyeon Park, Woojin Kim, Jaeik Kim +1
Despite significant advancements in Vision-Language Models (VLMs), the performance of existing VLMs remains hindered by object hallucination, a critical challenge to achieving accu…