4 papers · 1 filter
Decoupled Training with Local Reinforcement Fine-Tuning in Federated Learning
Yuting Ma, Lechao Cheng, Xiaohua Xu
Federated Learning (FL) with pre-trained Vision-Language Models (VLMs) has emerged as a promising paradigm for various downstream tasks. By leveraging its strong representations, r…
VDNeRF: Vision-only Dynamic Neural Radiance Field for Urban Scenes
Zhengyu Zou, Jingfeng Li, Hao Li +5
Neural Radiance Fields (NeRFs) implicitly model continuous three-dimensional scenes using a set of images with known camera poses, enabling the rendering of photorealistic novel vi…
FoPru: Focal Pruning for Efficient Large Vision-Language Models
Lei Jiang, Weizhe Huang, Tongxuan Liu +4
Large Vision-Language Models (LVLMs) represent a significant advancement toward achieving superior multimodal capabilities by enabling powerful Large Language Models (LLMs) to unde…
MarvelOVD: Marrying Object Recognition and Vision-Language Models for Robust Open-Vocabulary Object Detection
Kuo Wang, Lechao Cheng, Weikai Chen +4
Learning from pseudo-labels that generated with VLMs~(Vision Language Models) has been shown as a promising solution to assist open vocabulary detection (OVD) in recent studies. Ho…