most citedKnowledge-Enhanced Dual-stream Zero-shot Composed Image Retrieval

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

collaborators

6 papers

cs.CV2024

Joint Conditional Diffusion Model for Image Restoration with Mixed Degradations

Yufeng Yue, Meng Yu, Luojie Yang +1

Image restoration is rather challenging in adverse weather conditions, especially when multiple degradations occur simultaneously. Blind image decomposition was proposed to tackle…

cs.CV2024

Psychometry: An Omnifit Model for Image Reconstruction from Human Brain Activity

Ruijie Quan, Wenguan Wang, Zhibo Tian +2

Reconstructing the viewed images from human brain activity bridges human and computer vision through the Brain-Computer Interface. The inherent variability in brain function betwee…

cs.CV20241 cited

Clustering Propagation for Universal Medical Image Segmentation

Yuhang Ding, Liulei Li, Wenguan Wang +1

Prominent solutions for medical image segmentation are typically tailored for automatic or interactive setups, posing challenges in facilitating progress achieved in one task to an…

cs.CV20242 cited

Knowledge-Enhanced Dual-stream Zero-shot Composed Image Retrieval

Yucheng Suo, Fan Ma, Linchao Zhu +1

We study the zero-shot Composed Image Retrieval (ZS-CIR) task, which is to retrieve the target image given a reference image and a description without training on the triplet datas…

cs.CV20241 cited

MIGC: Multi-Instance Generation Controller for Text-to-Image Synthesis

Dewei Zhou, You Li, Fan Ma +2

We present a Multi-Instance Generation (MIG) task, simultaneously generating multiple instances with diverse controls in one image. Given a set of predefined coordinates and their…

cs.CV2024

GD^2-NeRF: Generative Detail Compensation via GAN and Diffusion for One-shot Generalizable Neural Radiance Fields

Xiao Pan, Zongxin Yang, Shuai Bai +1

In this paper, we focus on the One-shot Novel View Synthesis (O-NVS) task which targets synthesizing photo-realistic novel views given only one reference image per scene. Previous…