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20242026
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cs.CV2026

VideoResearcher: Self-Improving Tool Design for Long-Video Understanding

Dingqiang Ye, Dongdi Zhao, Kaishen Wang +11

Video agents have made substantial progress in long-video understanding. Yet effective video-agent systems require costly, time-consuming manual design and trial and error. Current…

cs.CV2026

Thermal-Det: Language-Guided Cross-Modal Distillation for Open-Vocabulary Thermal Object Detection

Yasiru Ranasinghe, Elim Schenck, Florence Yellin +3

Existing open-vocabulary detectors focus on RGB images and fail to generalize to thermal imagery, where low texture and emissivity variations challenge RGB-based semantics. We pres…

cs.CV2026

On-Policy Distillation with Best-of-N Teacher Rollout Selection

Ke Zhang, Yunjie Tian, Dongdi Zhao +4

On-policy distillation (OPD), which supervises a student on its own sampled trajectories, has emerged as a data-efficient post-training method for improving reasoning while avoidin…

cs.CV2025

ProCrop: Learning Aesthetic Image Cropping from Professional Compositions

Ke Zhang, Tianyu Ding, Jiachen Jiang +4

Image cropping is crucial for enhancing the visual appeal and narrative impact of photographs, yet existing rule-based and data-driven approaches often lack diversity or require an…

cs.CV2025

MedCL: Learning Consistent Anatomy Distribution for Scribble-supervised Medical Image Segmentation

Ke Zhang, Vishal M. Patel

Curating large-scale fully annotated datasets is expensive, laborious, and cumbersome, especially for medical images. Several methods have been proposed in the literature that make…

cs.CV2024

ModelMix: A New Model-Mixup Strategy to Minimize Vicinal Risk across Tasks for Few-scribble based Cardiac Segmentation

Ke Zhang, Vishal M. Patel

Pixel-level dense labeling is both resource-intensive and time-consuming, whereas weak labels such as scribble present a more feasible alternative to full annotations. However, tra…