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RobustFusion: Robust Volumetric Performance Reconstruction under Human-object Interactions
We present a robust volumetric performance reconstruction approach from a single RGBD stream, which solves the challenging ambiguity and occlusions under human-object interactions without pre-scanned templates.
submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
[Paper (Coming soon)]
[Project Page (Coming soon)]
[Video]
[Arxiv]
[bibtex (Coming soon)]
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SportsCap: Monocular 3D Motion Capture and Fine-Grained Understanding in Challenging Sports Videos
We present the first joint 3D motion capture and fine-grained understanding approach for various challenging sports movements from only a single RGB video input using mid-level sub-motion embedding analysis.
International Journal of Computer Vision (IJCV) , 2021.
[Paper]
[Project Page]
[Video]
[bibtex]
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GNeRF: GAN-based Neural Radiance Field without Posed Camera
We present GNeRF, a method that can estimate camera poses and neural radiance fields jointly when the cameras are initialized at random poses in complex scenarios (outside-in scenes with less texture or intense noise ).
International Conference on Computer Vision (ICCV), 2021. Oral
[Paper (Coming soon)]
[Project Page (Coming soon)]
[Video (Coming soon)]
[Arxiv]
[bibtex]
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Neural Video Portrait Relighting in Real-time via Consistency Modeling
We present a approach for realistic video portrait relighting into new scenes with dynamic illuminations in real-time even even on portable device by jointly modeling the semantic, temporal and lighting consistency.
International Conference on Computer Vision (ICCV), 2021.
[Paper (Coming soon)]
[Project Page]
[Video]
[Arxiv]
[bibtex]
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Neural Free-Viewpoint Performance Rendering under Complex Human-object Interactions
We present a human-object neural volumetric rendering using only sparse RGB cameras, which generates both high-quality geometry and photo-realistic texture of human activities in novel views for interaction scenarios.
ACM International Conference on Multimedia (ACMMM), 2021. Oral
[Paper (Coming soon)]
[Video (Coming soon)]
[bibtex (Coming soon)]
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iButter: Neural Interactive Bullet Time Generator for Human Free-viewpoint Rendering
We present an interactive bullet-time generator for human free-viewpoint rendering from multiple RGB streams. It enables trajectory-aware refinement and real-time dynamic NeRF rendering without tedious per-scene training.
ACM International Conference on Multimedia (ACMMM), 2021. Oral
[Paper (Coming soon)]
[Video (Coming soon)]
[bibtex (Coming soon)]
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Towards Controllable and Photorealistic Region-wise Image Manipulation
We build an auto-encoder for photorealistic region-wise style editing on real images, with the aid of code alignment loss and content consistency loss in a self-supervised manner to modulate the training process.
ACM International Conference on Multimedia (ACMMM), 2021.
[Paper (Coming soon)]
[Video (Coming soon)]
[bibtex (Coming soon)]
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Few-shot Neural Human Performance Rendering from Sparse RGBD Videos
We present the first few-shot neural human performance rendering approach using six sparse RGBD cameras which generates photorealistic texture of challenging human activities under the sparse capture setup.
International Joint Conferences on Artificial Intelligence Organization (IJCAI), 2021.
[Paper (Coming soon)]
[Project Page (Coming soon)]
[Video (Coming soon)]
[arXiv]
[bibtex]
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PIANO: A Parametric Hand Bone Model from Magnetic Resonance Imaging
We present PIANO, the first statistical hand bone model from MRI data, which is biologically correct, simple to animate, and differentiable. It enables anatomically fine-grained understanding of the hand kinematic structure.
International Joint Conferences on Artificial Intelligence Organization (IJCAI), 2021.
[Paper (Coming soon)]
[Project Page]
[Video]
[arXiv]
[bibtex]
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Editable Free-Viewpoint Video using a Layered Neural Representation
We present the first approach to generate editable photo-realistic free-viewpoint videos of large-scale dynamic scenes using a new neural layered representation,which enables numerous photo-realistic visual editing effects.
ACM Transactions on Graphics (Proc. of SIGGRAPH), 2021.
[Paper]
[Project Page]
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MirrorNeRF: One-shot Neural Portrait Radiance Field from Multi-mirror Catadioptric Imaging
We present a one-shot neural portrait rendering approach using a catadioptric imaging system with multiple sphere mirrors and a single high-resolution digital camera, which maintains low-cost and casual capture setting.
International Conference on Computational Photography (ICCP), 2021.
[Paper]
[Project Page (Coming soon)]
[Video]
[arXiv]
[bibtex]
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Convolutional Neural Opacity Radiance Fields
We present a novel scheme to generate convolutional neural opacity radiance fields for fuzzy objects, which combines explicit opacity modeling with NeRF for high-quality appearance and alpha mattes generation.
International Conference on Computational Photography (ICCP), 2021.
[Paper]
[Project Page (Coming soon)]
[Video]
[arXiv]
[bibtex]
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ChallenCap: Monocular 3D Capture of Challenging Human Performances using Multi-Modal References
We propose a robust monocualr human motion capture scheme for challenging scenarios with with extreme poses and complex motion patterns, which embrances multi-modal references in a data-driven manner.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. Oral
[Paper]
[Project Page (Coming soon)]
[Video]
[arXiv]
[bibtex]
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NeuralHumanFVV: Real-Time Neural Volumetric Human Performance Rendering using RGB Cameras
We present a real-time human neural volumetric rendering system using only sparse RGB cameras, which generates both high-quality geometry and photo-realistic texture of human activities in arbitrary novel views.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
[Paper]
[Project Page (Coming soon)]
[Video]
[arXiv]
[bibtex]
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