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Explicit Correspondence Matching for Generalizable Neural Radiance Fields
Yuedong Chen,
Haofei Xu,
Qianyi Wu,
Chuanxia Zheng,
Tat-Jen Cham,
Jianfei Cai
arXiv, 2023
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Employing explicit correspondence matching as a geometry prior enables NeRF to generalize across scenes.
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Unifying Flow, Stereo and Depth Estimation
Haofei Xu,
Jing Zhang,
Jianfei Cai,
Hamid Rezatofighi,
Fisher Yu,
Dacheng Tao,
Andreas Geiger
arXiv, 2022
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A unified dense correspondence matching formulation enables three motion and 3D perception tasks to be solved with a unified model.
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GMFlow: Learning Optical Flow via Global Matching
Haofei Xu,
Jing Zhang,
Jianfei Cai,
Hamid Rezatofighi,
Dacheng Tao
Computer Vision and Pattern Recognition (CVPR), 2022 (Oral)
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Learning strong features with a Transformer enables optical flow to be obtained by directly comparing feature similarities.
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High-Resolution Optical Flow from 1D Attention and Correlation
Haofei Xu,
Jiaolong Yang,
Jianfei Cai,
Juyong Zhang,
Xin Tong
International Conference on Computer Vision (ICCV), 2021 (Oral)
code
Factorizing 2D optical flow with 1D attention and 1D correlation enables 4K resolution optical flow estimation on ordinary GPUs.
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Recurrent Multi-view Alignment Network for Unsupervised Surface Registration
Wanquan Feng,
Juyong Zhang,
Hongrui Cai,
Haofei Xu,
Junhui Hou,
Hujun Bao
Computer Vision and Pattern Recognition (CVPR), 2021
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A new non-rigid representation and a differentiable loss function enable end-to-end learning of non-rigid registration.
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AANet: Adaptive Aggregation Network for Efficient Stereo Matching
Haofei Xu,
Juyong Zhang
Computer Vision and Pattern Recognition (CVPR), 2020
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A sparse points-based cost aggregation method leads to an efficient and accurate stereo matching architecture without any 3D convolutions.
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Region Deformer Networks for Unsupervised Depth Estimation from Unconstrained Monocular Videos
Haofei Xu,
Jianmin Zheng,
Jianfei Cai,
Juyong Zhang
International Joint Conference on Artificial Intelligence (IJCAI), 2019
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A bicubic motion representation enables unsupervised depth estimation from monocular videos in dynamic scenes.
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Invited Talks
- Unifying Flow, Stereo and Depth Estimation [slides] [video(cn)],
机器之心, 2022.12.28
- GMFlow: Learning Optical Flow via Global Matching [slides], Monash University, 2022.04.13
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Academic Services
- Conference Reviewer: ICCV 2021, CVPR 2022, ECCV 2022, CVPR 2023
- Journal Reviewer: TIP, IJCV
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