no code implementations • 19 Feb 2024 • Chong Zeng, Yue Dong, Pieter Peers, Youkang Kong, Hongzhi Wu, Xin Tong
To provide the content creator with fine-grained control over the lighting during image generation, we augment the text-prompt with detailed lighting information in the form of radiance hints, i. e., visualizations of the scene geometry with a homogeneous canonical material under the target lighting.
1 code implementation • 6 Oct 2023 • Haiwei Zhang, Jiqing Zhang, Bo Dong, Pieter Peers, Wenwei Wu, Xiaopeng Wei, Felix Heide, Xin Yang
To the best of our knowledge, our method is the first eye-based emotion recognition method that leverages event-based cameras and spiking neural network.
1 code implementation • 25 Aug 2023 • Chong Zeng, Guojun Chen, Yue Dong, Pieter Peers, Hongzhi Wu, Xin Tong
This paper presents a novel neural implicit radiance representation for free viewpoint relighting from a small set of unstructured photographs of an object lit by a moving point light source different from the view position.
no code implementations • ICCV 2023 • Zhaoxuan Zhang, Bo Dong, Tong Li, Felix Heide, Pieter Peers, BaoCai Yin, Xin Yang
In this paper, we present Iterative Symmetry Completion Network (ISCNet), a single depth-image shape completion method that exploits reflective symmetry cues to obtain more detailed shapes.
no code implementations • ICCV 2023 • Yu Qiao, Bo Dong, Ao Jin, Yu Fu, Seung-Hwan Baek, Felix Heide, Pieter Peers, Xiaopeng Wei, Xin Yang
In this paper, we present the first polarization-guided video glass segmentation propagation solution (PGVS-Net) that can robustly and coherently propagate glass segmentation in RGB-P video sequences.
no code implementations • CVPR 2022 • Haiyang Mei, Bo Dong, Wen Dong, Jiaxi Yang, Seung-Hwan Baek, Felix Heide, Pieter Peers, Xiaopeng Wei, Xin Yang
Transparent and semi-transparent materials pose significant challenges for existing scene understanding and segmentation algorithms due to their lack of RGB texture which impedes the extraction of meaningful features.
Ranked #14 on Semantic Segmentation on KITTI-360
no code implementations • CVPR 2021 • Haiyang Mei, Bo Dong, Wen Dong, Pieter Peers, Xin Yang, Qiang Zhang, Xiaopeng Wei
To exploit depth information in mirror segmentation, we first construct a large-scale RGB-D mirror segmentation dataset, which we subsequently employ to train a novel depth-aware mirror segmentation framework.
no code implementations • CVPR 2019 • Xiao Li, Yue Dong, Pieter Peers, Xin Tong
Key to our method is a novel multi-projection generative adversarial network (MP-GAN) that trains a 3D shape generator to be consistent with multiple 2D projections of the 3D shapes, and without direct access to these 3D shapes.
no code implementations • CVPR 2014 • Bo Dong, Kathleen D. Moore, Weiyi Zhang, Pieter Peers
This paper proposes a novel photometric stereo solution to jointly estimate surface normals and scattering parameters from a globally planar, homogeneous, translucent object.