1 code implementation • CVPR 2021 • Gang Fu, Qing Zhang, Lei Zhu, Ping Li, Chunxia Xiao
Specular highlight detection and removal are fundamental and challenging tasks.
1 code implementation • CVPR 2019 • Wenxiao Zhang, Chunxia Xiao
Point cloud based retrieval for place recognition is an emerging problem in vision field.
Ranked #9 on
3D Place Recognition
on Oxford RobotCar Dataset
(AR@1% metric)
1 code implementation • ECCV 2020 • Wenxiao Zhang, Qingan Yan, Chunxia Xiao
In this work, instead of using a global feature to recover the whole complete surface, we explore the functionality of multi-level features and aggregate different features to represent the known part and the missing part separately.
1 code implementation • CVPR 2017 • Qingan Yan, Long Yang, Ling Zhang, Chunxia Xiao
A perennial problem in structure from motion (SfM) is visual ambiguity posed by repetitive structures.
3 code implementations • 20 Nov 2019 • Ling Zhang, Chengjiang Long, Xiaolong Zhang, Chunxia Xiao
To our best knowledge, we are the first one to explore residual and illumination for shadow removal.
1 code implementation • CVPR 2023 • Ling Zhang, Yinghao He, Qing Zhang, Zheng Liu, Xiaolong Zhang, Chunxia Xiao
In this paper, we present a color-aware background extraction network (CBENet) for extracting a spatially varying background image that accurately depicts the background colors of the document.
1 code implementation • ICCV 2023 • Gang Fu, Qing Zhang, Lei Zhu, Chunxia Xiao, Ping Li
This paper aims to remove specular highlights from a single object-level image.
1 code implementation • 14 Sep 2021 • Hanning Yu, Wentao Liu, Chengjiang Long, Bo Dong, Qin Zou, Chunxia Xiao
Based on this observation, we propose a novel normalization method called " HDR calibration " for HDR images stored in relative luminance, calibrating HDR images into a similar luminance scale according to the LDR images.
1 code implementation • ICCV 2021 • Zipei Chen, Chengjiang Long, Ling Zhang, Chunxia Xiao
In this paper, we propose a novel two-stage context-aware network named CANet for shadow removal, in which the contextual information from non-shadow regions is transferred to shadow regions at the embedded feature spaces.
1 code implementation • CVPR 2022 • Xiao Lu, Yihong Cao, Sheng Liu, Chengjiang Long, Zipei Chen, Xuanyu Zhou, Yimin Yang, Chunxia Xiao
Our proposed approach is extensively validated on the ViSha dataset and a self-annotated dataset.
1 code implementation • 5 Aug 2021 • Xinzhi Dong, Chengjiang Long, Wenju Xu, Chunxia Xiao
With the well-designed Dual-GCN, we can make the linguistic transformer better understand the relationship between different objects in a single image and make full use of similar images as auxiliary information to generate a reasonable caption description for a single image.
no code implementations • CVPR 2018 • Yanping Fu, Qingan Yan, Long Yang, Jie Liao, Chunxia Xiao
Acquiring realistic texture details for 3D models is important in 3D reconstruction.
no code implementations • 25 Jul 2019 • Qing Zhang, Yongwei Nie, Lei Zhu, Chunxia Xiao, Wei-Shi Zheng
To obtain high-quality results free of these artifacts, we present a novel underexposed photo enhancement approach that is able to maintain the perceptual consistency.
no code implementations • 26 Jul 2019 • Tao Hu, Chengjiang Long, Leheng Zhang, Chunxia Xiao
In this paper, we propose a novel way to interpret text information by extracting visual feature presentation from multiple high-resolution and photo-realistic synthetic images generated by Text-to-image Generative Adversarial Network (GAN) to improve the performance of image labeling.
no code implementations • ICCV 2019 • Bin Ding, Chengjiang Long, Ling Zhang, Chunxia Xiao
In this paper we propose an attentive recurrent generative adversarial network (ARGAN) to detect and remove shadows in an image.
Generative Adversarial Network
Shadow Detection And Removal
+1
no code implementations • 28 Jul 2021 • Tao Hu, Chengjiang Long, Chunxia Xiao
Based on those constraints, a category-consistent and relativistic diverse conditional GAN (CRD-CGAN) is proposed to synthesize $K$ photo-realistic images simultaneously.
no code implementations • CVPR 2022 • Zhongyun Bao, Chengjiang Long, Gang Fu, Daquan Liu, Yuanzhen Li, Jiaming Wu, Chunxia Xiao
Specifically, we firstly apply a physically-based rendering method to construct a large-scale, high-quality dataset (named IH) for our task, which contains various types of foreground objects and background scenes with different lighting conditions.
no code implementations • CVPR 2022 • Tuo Cao, Fei Luo, Yanping Fu, Wenxiao Zhang, Shengjie Zheng, Chunxia Xiao
To this end, we proposed a Depth-Guided Edge Convolutional Network (DGECN) for 6D pose estimation task.
no code implementations • 13 Oct 2022 • Yusen Wang, Zongcheng Li, Yu Jiang, Kaixuan Zhou, Tuo Cao, Yanping Fu, Chunxia Xiao
Recently, implicit neural representations have become a promising way to reconstruct surfaces from multiview images due to their high-quality results and simplicity.
no code implementations • ICCV 2023 • Zongcheng Li, Xiaoxiao Long, Yusen Wang, Tuo Cao, Wenping Wang, Fei Luo, Chunxia Xiao
In this paper, we propose to leverage implicit Signed Distance Function (SDF) as surface representation, and optimize the SDF field via volume rendering with a self-occlusion aware refractive ray tracing.
no code implementations • ICCV 2023 • Ziqi Wang, Fei Luo, Xiaoxiao Long, Wenxiao Zhang, Chunxia Xiao
Due to the limited resolution of 3D sensors and the inevitable mutual occlusion between objects, 3D scans of real scenes are commonly incomplete.
no code implementations • 19 Dec 2023 • Chunjie Luo, Fei Luo, Yusen Wang, Enxu Zhao, Chunxia Xiao
To model the deformation more accurately, we propose to initialize an estimated 3D clothed human in the canonical space, as it is easier for deformation fields to learn from the clothed human than from SMPL.