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cs.CV2026

Video Parallel Scaling: Aggregating Diverse Frame Subsets for VideoLLMs

Hyungjin Chung, Hyelin Nam, Jiyeon Kim +6

Video Large Language Models (VideoLLMs) face a critical bottleneck: increasing the number of input frames to capture fine-grained temporal detail leads to prohibitive computational…

cs.CV2026

Event-based Facial Keypoint Alignment via Cross-Modal Fusion Attention and Self-Supervised Multi-Event Representation Learning

Donghwa Kang, Junho Kim, Dongwoo Kang

Event cameras offer unique advantages for facial keypoint alignment under challenging conditions, such as low light and rapid motion, due to their high temporal resolution and robu…

cs.CV2026

CAPA: Contribution-Aware Pruning and FFN Approximation for Efficient Large Vision-Language Models

Samyak Jha, Junho Kim

Efficient inference in Large Vision-Language Models is constrained by the high cost of processing thousands of visual tokens, yet it remains unclear which tokens and computations c…

cs.CV2025

CapeLLM: Support-Free Category-Agnostic Pose Estimation with Multimodal Large Language Models

Junho Kim, Hyungjin Chung, Byung-Hoon Kim

Category-agnostic pose estimation (CAPE) has traditionally relied on support images with annotated keypoints, a process that is often cumbersome and may fail to fully capture the n…

cs.CV2024

D-Cube: Exploiting Hyper-Features of Diffusion Model for Robust Medical Classification

Minhee Jang, Juheon Son, Thanaporn Viriyasaranon +2

The integration of deep learning technologies in medical imaging aims to enhance the efficiency and accuracy of cancer diagnosis, particularly for pancreatic and breast cancers, wh…