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Peter Anderson | CVPR 2021 Embodied AI Workshop Talk
Autolabeling 3D Objects With Differentiable Rendering of SDF Shape Priors (CVPR 2020 Oral)
CVPR 2021 Poster: Learning Optical Flow from a Few Matches (Jiang et al.)
DIST: Rendering Deep Implicit Signed Distance Function With Differentiable Sphere Tracing
[SIGGRAPH Asia 2021] Differentiable Transient Rendering
Structure-guided Ranking Loss for Single Image Depth Prediction (CVPR 2020)
[CVPR 2021] Holistic 3D Scene Understanding from a Single Image with Implicit Representation
Physics-Guided Diffusion Model for Darcy Flow PDE Explained [Sparse Sensors]
Differentiable Shadow Mapping for Efficient Inverse Graphics (CVPR 2023)
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Last Updated: September 24, 2026
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All presented materials are available at the UnsupervisedR&R: Unsupervised Point Cloud Registration via Peter Anderson is a Research Scientist in the Language team at Google Research. His research interests include computer vision ... In this work, we present an automatic annotation pipeline to recover 9D cuboids and 3D shapes from pre-trained off-the-shelf 2D ... Learning Optical Flow from a Few Matches Shihao Jiang, Yao Lu, Hongdong Li and Richard Hartley At the IEEE Conference on ... Learn all the ways Microsoft is a part of The project page: kexianhust.github.io/Structure-Guided-Ranking-Loss/ Single image depth prediction is a challenging task ... Get the free Jupyter notebook for this video: notebooks.compu-flair.com/diffusion-part4 ...
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