most citedRegionBLIP: A Unified Multi-modal Pre-training Framework for Holistic and Regional Comprehension

4 citations · 10 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CV20232 cited

Viewpoint Integration and Registration with Vision Language Foundation Model for Image Change Understanding

Xiaonan Lu, Jianlong Yuan, Ruigang Niu +2

Recently, the development of pre-trained vision language foundation models (VLFMs) has led to remarkable performance in many tasks. However, these models tend to have strong single…

eess.IV2023

Temporal compressive edge imaging enabled by a lensless diffuser camera

Ze Zheng, Baolei Liu, Jiaqi Song +4

Lensless imagers based on diffusers or encoding masks enable high-dimensional imaging from a single shot measurement and have been applied in various applications. However, to furt…

cs.CV20232 cited

ICPC: Instance-Conditioned Prompting with Contrastive Learning for Semantic Segmentation

Chaohui Yu, Qiang Zhou, Zhibin Wang +1

Modern supervised semantic segmentation methods are usually finetuned based on the supervised or self-supervised models pre-trained on ImageNet. Recent work shows that transferring…

cs.CV20234 cited

RegionBLIP: A Unified Multi-modal Pre-training Framework for Holistic and Regional Comprehension

Qiang Zhou, Chaohui Yu, Shaofeng Zhang +3

In this work, we investigate extending the comprehension of Multi-modal Large Language Models (MLLMs) to regional objects. To this end, we propose to extract features corresponding…

physics.optics20231 cited

Quantitative and dark field ghost imaging with ultraviolet light

Jiaqi Song, Baolei Liu, Yao Wang +5

Ultraviolet (UV) imaging enables a diverse array of applications, such as material composition analysis, biological fluorescence imaging, and detecting defects in semiconductor man…

cs.CV2023

Improved Neural Radiance Fields Using Pseudo-depth and Fusion

Jingliang Li, Qiang Zhou, Chaohui Yu +4

Since the advent of Neural Radiance Fields, novel view synthesis has received tremendous attention. The existing approach for the generalization of radiance field reconstruction pr…