54 citations · 131 across the 84 of their papers we have counts for
16 papers · 1 filter
Self-supervised Learning for Enhancing Geometrical Modeling in 3D-Aware Generative Adversarial Network
Jiarong Guo, Xiaogang Xu, Hengshuang Zhao
3D-aware Generative Adversarial Networks (3D-GANs) currently exhibit artifacts in their 3D geometrical modeling, such as mesh imperfections and holes. These shortcomings are primar…
CorresNeRF: Image Correspondence Priors for Neural Radiance Fields
Yixing Lao, Xiaogang Xu, Zhipeng Cai +2
Neural Radiance Fields (NeRFs) have achieved impressive results in novel view synthesis and surface reconstruction tasks. However, their performance suffers under challenging scena…
LucidDreamer: Towards High-Fidelity Text-to-3D Generation via Interval Score Matching
Yixun Liang, Xin Yang, Jiantao Lin +3
The recent advancements in text-to-3D generation mark a significant milestone in generative models, unlocking new possibilities for creating imaginative 3D assets across various re…
Restoration-Oriented Video Frame Interpolation with Region-Distinguishable Priors from SAM
Yan Han, Xiaogang Xu, Yingqi Lin +3
In existing restoration-oriented Video Frame Interpolation (VFI) approaches, the motion estimation between neighboring frames plays a crucial role. However, the estimation accuracy…
Geometric-Aware Low-Light Image and Video Enhancement via Depth Guidance
Yingqi Lin, Xiaogang Xu, Jiafei Wu +2
Low-Light Enhancement (LLE) is aimed at improving the quality of photos/videos captured under low-light conditions. It is worth noting that most existing LLE methods do not take ad…
An Incremental Unified Framework for Small Defect Inspection
Jiaqi Tang, Hao Lu, Xiaogang Xu +7
Artificial Intelligence (AI)-driven defect inspection is pivotal in industrial manufacturing. Yet, many methods, tailored to specific pipelines, grapple with diverse product portfo…
Diffusion Noise Feature: Accurate and Fast Generated Image Detection
Yichi Zhang, Xiaogang Xu
Generative models now produce images with such stunning realism that they can easily deceive the human eye. While this progress unlocks vast creative potential, it also presents si…
Refine, Discriminate and Align: Stealing Encoders via Sample-Wise Prototypes and Multi-Relational Extraction
Shuchi Wu, Chuan Ma, Kang Wei +4
This paper introduces RDA, a pioneering approach designed to address two primary deficiencies prevalent in previous endeavors aiming at stealing pre-trained encoders: (1) suboptima…
Clarity ChatGPT: An Interactive and Adaptive Processing System for Image Restoration and Enhancement
Yanyan Wei, Zhao Zhang, Jiahuan Ren +5
The generalization capability of existing image restoration and enhancement (IRE) methods is constrained by the limited pre-trained datasets, making it difficult to handle agnostic…
FreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models
Lihe Yang, Xiaogang Xu, Bingyi Kang +2
Semantic segmentation has witnessed tremendous progress due to the proposal of various advanced network architectures. However, they are extremely hungry for delicate annotations t…
SSL-Auth: An Authentication Framework by Fragile Watermarking for Pre-trained Encoders in Self-supervised Learning
Xiaobei Li, Changchun Yin, Liyue Zhu +4
Self-supervised learning (SSL), a paradigm harnessing unlabeled datasets to train robust encoders, has recently witnessed substantial success. These encoders serve as pivotal featu…
High Dynamic Range Image Reconstruction via Deep Explicit Polynomial Curve Estimation
Jiaqi Tang, Xiaogang Xu, Sixing Hu +1
Due to limited camera capacities, digital images usually have a narrower dynamic illumination range than real-world scene radiance. To resolve this problem, High Dynamic Range (HDR…
Lighting up NeRF via Unsupervised Decomposition and Enhancement
Haoyuan Wang, Xiaogang Xu, Ke Xu +1
Neural Radiance Field (NeRF) is a promising approach for synthesizing novel views, given a set of images and the corresponding camera poses of a scene. However, images photographed…
Low-Light Image Enhancement via Structure Modeling and Guidance
Xiaogang Xu, Ruixing Wang, Jiangbo Lu
This paper proposes a new framework for low-light image enhancement by simultaneously conducting the appearance as well as structure modeling. It employs the structural feature to…
TriVol: Point Cloud Rendering via Triple Volumes
Tao Hu, Xiaogang Xu, Ruihang Chu +1
Existing learning-based methods for point cloud rendering adopt various 3D representations and feature querying mechanisms to alleviate the sparsity problem of point clouds. Howeve…
Point2Pix: Photo-Realistic Point Cloud Rendering via Neural Radiance Fields
Tao Hu, Xiaogang Xu, Shu Liu +1
Synthesizing photo-realistic images from a point cloud is challenging because of the sparsity of point cloud representation. Recent Neural Radiance Fields and extensions are propos…