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06/05/2023
MotionDiffuser: Controllable Multi-Agent Motion Prediction using Diffusion
We present MotionDiffuser, a diffusion based representation for the join...
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12/06/2022
NeRDi: Single-View NeRF Synthesis with Language-Guided Diffusion as General Image Priors
2D-to-3D reconstruction is an ill-posed problem, yet humans are good at ...
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11/28/2022
OpenScene: 3D Scene Understanding with Open Vocabularies
Traditional 3D scene understanding approaches rely on labeled 3D dataset...
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10/15/2022
Improving the Intra-class Long-tail in 3D Detection via Rare Example Mining
Continued improvements in deep learning architectures have steadily adva...
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06/07/2021
Shape As Points: A Differentiable Poisson Solver
In recent years, neural implicit representations gained popularity in 3D...
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06/14/2020
ShapeFlow: Learnable Deformations Among 3D Shapes
We present ShapeFlow, a flow-based model for learning a deformation spac...
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05/23/2020
MeshODE: A Robust and Scalable Framework for Mesh Deformation
We present MeshODE, a scalable and robust framework for pairwise CAD mod...
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05/01/2020
MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework
We propose MeshfreeFlowNet, a novel deep learning-based super-resolution...
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03/19/2020
Local Implicit Grid Representations for 3D Scenes
Shape priors learned from data are commonly used to reconstruct 3D objec...
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03/18/2020
Adversarial Texture Optimization from RGB-D Scans
Realistic color texture generation is an important step in RGB-D surface...
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01/30/2019
DDSL: Deep Differentiable Simplex Layer for Learning Geometric Signals
We present a Deep Differentiable Simplex Layer (DDSL) for neural network...
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01/07/2019
Convolutional Neural Networks on non-uniform geometrical signals using Euclidean spectral transformation
Convolutional Neural Networks (CNN) have been successful in processing d...
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01/07/2019
Spherical CNNs on Unstructured Grids
We present an efficient convolution kernel for Convolutional Neural Netw...
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09/22/2017