3 papers
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.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…
cs.CV2024
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…