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Spectral Unions of Partial Deformable 3D Shapes
Spectral geometric methods have brought revolutionary changes to the fie...
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Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels
The success of learning with noisy labels (LNL) methods relies heavily o...
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Weakly Supervised Learning of Rigid 3D Scene Flow
We propose a data-driven scene flow estimation algorithm exploiting the ...
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Self-Supervised Equivariant Scene Synthesis from Video
We propose a self-supervised framework to learn scene representations fr...
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Human 3D keypoints via spatial uncertainty modeling
We introduce a technique for 3D human keypoint estimation that directly ...
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3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection
3D object detection is an important yet demanding task that heavily reli...
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Non-Rigid Puzzles
Shape correspondence is a fundamental problem in computer graphics and v...
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Learned Equivariant Rendering without Transformation Supervision
We propose a self-supervised framework to learn scene representations fr...
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ReLMoGen: Leveraging Motion Generation in Reinforcement Learning for Mobile Manipulation
Many Reinforcement Learning (RL) approaches use joint control signals (p...
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PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding
Arguably one of the top success stories of deep learning is transfer lea...
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Object-Centric Multi-View Aggregation
We present an approach for aggregating a sparse set of views of an objec...
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Representation Learning Through Latent Canonicalizations
We seek to learn a representation on a large annotated data source that ...
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On Learning Sets of Symmetric Elements
Learning from unordered sets is a fundamental learning setup, which is a...
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Continuous Geodesic Convolutions for Learning on 3D Shapes
The majority of descriptor-based methods for geometric processing of non...
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ImVoteNet: Boosting 3D Object Detection in Point Clouds with Image Votes
3D object detection has seen quick progress thanks to advances in deep l...
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The Whole Is Greater Than the Sum of Its Nonrigid Parts
According to Aristotle, a philosopher in Ancient Greece, "the whole is g...
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Deep Hough Voting for 3D Object Detection in Point Clouds
Current 3D object detection methods are heavily influenced by 2D detecto...
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Self-supervised Learning of Dense Shape Correspondence
We introduce the first completely unsupervised correspondence learning a...
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Class-Aware Fully-Convolutional Gaussian and Poisson Denoising
We propose a fully-convolutional neural-network architecture for image d...
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Dual-Primal Graph Convolutional Networks
In recent years, there has been a surge of interest in developing deep l...
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SOSELETO: A Unified Approach to Transfer Learning and Training with Noisy Labels
We present SOSELETO (SOurce SELEction for Target Optimization), a new me...
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Deformable Shape Completion with Graph Convolutional Autoencoders
The availability of affordable and portable depth sensors has made scann...
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Efficient Deformable Shape Correspondence via Kernel Matching
We present a method to match three dimensional shapes under non-isometri...
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Deep Class Aware Denoising
The increasing demand for high image quality in mobile devices brings fo...
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Deep Convolutional Denoising of Low-Light Images
Poisson distribution is used for modeling noise in photon-limited imagin...
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Cloud Dictionary: Sparse Coding and Modeling for Point Clouds
With the development of range sensors such as LIDAR and time-of-flight c...
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FPGA system for real-time computational extended depth of field imaging using phase aperture coding
We present a proof-of-concept end-to-end system for computational extend...
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Image reconstruction from dense binary pixels
Recently, the dense binary pixel Gigavision camera had been introduced, ...
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ASIST: Automatic Semantically Invariant Scene Transformation
We present ASIST, a technique for transforming point clouds by replacing...
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A Picture is Worth a Billion Bits: Real-Time Image Reconstruction from Dense Binary Pixels
The pursuit of smaller pixel sizes at ever increasing resolution in digi...
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