2 papers
cs.CV2026
Re-calibrated Contrastive Loss for Transformation-Aware Prompt Conditioning in Vision-Language Models
Seungmin Oh, Seunghun Kang, Jongbin Ryu
Ensuring effective transfer learning for vision-language models without compromising their generalization performance is crucial. However, many existing methods overlook data chara…
cs.CV2026
Evaluation of Winning Solutions of 2025 Low Power Computer Vision Challenge
Zihao Ye, Yung-Hsiang Lu, Xiao Hu +14
The IEEE Low-Power Computer Vision Challenge (LPCVC) aims to promote the development of efficient vision models for edge devices, balancing accuracy with constraints such as latenc…