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08/28/2023
HoloFusion: Towards Photo-realistic 3D Generative Modeling
Diffusion-based image generators can now produce high-quality and divers...
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07/22/2023
Replay: Multi-modal Multi-view Acted Videos for Casual Holography
We introduce Replay, a collection of multi-view, multi-modal videos of h...
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06/27/2023
PoseDiffusion: Solving Pose Estimation via Diffusion-aided Bundle Adjustment
Camera pose estimation is a long-standing computer vision problem that t...
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03/29/2023
HoloDiffusion: Training a 3D Diffusion Model using 2D Images
Diffusion models have emerged as the best approach for generative modeli...
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03/21/2023
Real-time volumetric rendering of dynamic humans
We present a method for fast 3D reconstruction and real-time rendering o...
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12/06/2022
Self-Supervised Correspondence Estimation via Multiview Registration
Video provides us with the spatio-temporal consistency needed for visual...
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11/07/2022
Common Pets in 3D: Dynamic New-View Synthesis of Real-Life Deformable Categories
Obtaining photorealistic reconstructions of objects from sparse views is...
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06/04/2022
Nerfels: Renderable Neural Codes for Improved Camera Pose Estimation
This paper presents a framework that combines traditional keypoint-based...
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04/05/2022
iSDF: Real-Time Neural Signed Distance Fields for Robot Perception
We present iSDF, a continual learning system for real-time signed distan...
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09/01/2021
Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction
Traditional approaches for learning 3D object categories have been predo...
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08/31/2021
DensePose 3D: Lifting Canonical Surface Maps of Articulated Objects to the Third Dimension
We tackle the problem of monocular 3D reconstruction of articulated obje...
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06/17/2021
Discovering Relationships between Object Categories via Universal Canonical Maps
We tackle the problem of learning the geometry of multiple categories of...
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06/17/2021
NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go
We present NeuroMorph, a new neural network architecture that takes as i...
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03/30/2021
Unsupervised Learning of 3D Object Categories from Videos in the Wild
Our goal is to learn a deep network that, given a small number of images...
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11/24/2020
Continuous Surface Embeddings
In this work, we focus on the task of learning and representing dense co...
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11/20/2020
RidgeSfM: Structure from Motion via Robust Pairwise Matching Under Depth Uncertainty
We consider the problem of simultaneously estimating a dense depth map a...
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11/02/2020
3D Multi-bodies: Fitting Sets of Plausible 3D Human Models to Ambiguous Image Data
We consider the problem of obtaining dense 3D reconstructions of humans ...
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08/28/2020
Canonical 3D Deformer Maps: Unifying parametric and non-parametric methods for dense weakly-supervised category reconstruction
We propose the Canonical 3D Deformer Map, a new representation of the 3D...
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07/16/2020
Accelerating 3D Deep Learning with PyTorch3D
Deep learning has significantly improved 2D image recognition. Extending...
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09/05/2019
C3DPO: Canonical 3D Pose Networks for Non-Rigid Structure From Motion
We propose C3DPO, a method for extracting 3D models of deformable object...
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07/27/2018
Semi-convolutional Operators for Instance Segmentation
Object detection and instance segmentation are dominated by region-based...
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04/04/2018
Self-supervised Learning of Geometrically Stable Features Through Probabilistic Introspection
Self-supervision can dramatically cut back the amount of manually-labell...
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05/10/2017
Learning 3D Object Categories by Looking Around Them
Traditional approaches for learning 3D object categories use either synt...
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07/05/2016
Learning the semantic structure of objects from Web supervision
While recent research in image understanding has often focused on recogn...
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04/27/2015
Cascaded Sparse Spatial Bins for Efficient and Effective Generic Object Detection
A novel efficient method for extraction of object proposals is introduce...
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04/18/2015
