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Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes
Neural signed distance functions (SDFs) are emerging as an effective rep...
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Personalized Federated Learning with First Order Model Optimization
While federated learning traditionally aims to train a single global mod...
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UniCon: Universal Neural Controller For Physics-based Character Motion
The field of physics-based animation is gaining importance due to the in...
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Emergent Road Rules In Multi-Agent Driving Environments
For autonomous vehicles to safely share the road with human drivers, aut...
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Learning Deformable Tetrahedral Meshes for 3D Reconstruction
3D shape representations that accommodate learning-based 3D reconstructi...
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Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration
In this paper, we introduce Watch-And-Help (WAH), a challenge for testin...
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The efficacy of Neural Planning Metrics: A meta-analysis of PKL on nuScenes
A high-performing object detection system plays a crucial role in autono...
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Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering
Differentiable rendering has paved the way to training neural networks t...
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Fed-Sim: Federated Simulation for Medical Imaging
Labelling data is expensive and time consuming especially for domains su...
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Interactive Annotation of 3D Object Geometry using 2D Scribbles
Inferring detailed 3D geometry of the scene is crucial for robotics appl...
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ScribbleBox: Interactive Annotation Framework for Video Object Segmentation
Manually labeling video datasets for segmentation tasks is extremely tim...
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Beyond Fixed Grid: Learning Geometric Image Representation with a Deformable Grid
In modern computer vision, images are typically represented as a fixed u...
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Meta-Sim2: Unsupervised Learning of Scene Structure for Synthetic Data Generation
Procedural models are being widely used to synthesize scenes for graphic...
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Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3D
The goal of perception for autonomous vehicles is to extract semantic re...
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Learning to Simulate Dynamic Environments with GameGAN
Simulation is a crucial component of any robotic system. In order to sim...
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Learning to Evaluate Perception Models Using Planner-Centric Metrics
Variants of accuracy and precision are the gold-standard by which the co...
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Neural Data Server: A Large-Scale Search Engine for Transfer Learning Data
Transfer learning has proven to be a successful technique to train deep ...
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The Shmoop Corpus: A Dataset of Stories with Loosely Aligned Summaries
Understanding stories is a challenging reading comprehension problem for...
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CrevNet: Conditionally Reversible Video Prediction
Applying resolution-preserving blocks is a common practice to maximize i...
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DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation
In this paper, we propose the differentiable mask-matching network (DMM-...
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A Theoretical Analysis of the Number of Shots in Few-Shot Learning
Few-shot classification is the task of predicting the category of an exa...
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Video Face Clustering with Unknown Number of Clusters
Understanding videos such as TV series and movies requires analyzing who...
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Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer
Many machine learning models operate on images, but ignore the fact that...
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Gated-SCNN: Gated Shape CNNs for Semantic Segmentation
Current state-of-the-art methods for image segmentation form a dense ima...
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Neural Graph Evolution: Towards Efficient Automatic Robot Design
Despite the recent successes in robotic locomotion control, the design o...
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EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis
Reducing the test time resource requirements of a neural network while p...
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DARNet: Deep Active Ray Network for Building Segmentation
In this paper, we propose a Deep Active Ray Network (DARNet) for automat...
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Meta-Sim: Learning to Generate Synthetic Datasets
Training models to high-end performance requires availability of large l...
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Devil is in the Edges: Learning Semantic Boundaries from Noisy Annotations
We tackle the problem of semantic boundary prediction, which aims to ide...
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Action Recognition from Single Timestamp Supervision in Untrimmed Videos
Recognising actions in videos relies on labelled supervision during trai...
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Mimicking the In-Camera Color Pipeline for Camera-Aware Object Compositing
We present a method for compositing virtual objects into a photograph su...
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Fast Interactive Object Annotation with Curve-GCN
Manually labeling objects by tracing their boundaries is a laborious pro...
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ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning
Sparse reward is one of the most challenging problems in reinforcement l...
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A Face-to-Face Neural Conversation Model
Neural networks have recently become good at engaging in dialog. However...
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SurfConv: Bridging 3D and 2D Convolution for RGBD Images
We tackle the problem of using 3D information in convolutional neural ne...
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Lifelong Learning for Image Captioning by Asking Natural Language Questions
In order to bring artificial agents into our lives, we will need to go b...
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A Neural Compositional Paradigm for Image Captioning
Mainstream captioning models often follow a sequential structure to gene...
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Pose Estimation for Objects with Rotational Symmetry
Pose estimation is a widely explored problem, enabling many robotic task...
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VirtualHome: Simulating Household Activities via Programs
In this paper, we are interested in modeling complex activities that occ...
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Color Sails: Discrete-Continuous Palettes for Deep Color Exploration
We present color sails, a discrete-continuous color gamut representation...
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Progressive Reasoning by Module Composition
Humans learn to solve tasks of increasing complexity by building on top ...
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Scaling Egocentric Vision: The EPIC-KITCHENS Dataset
First-person vision is gaining interest as it offers a unique viewpoint ...
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Efficient Interactive Annotation of Segmentation Datasets with Polygon-RNN++
Manually labeling datasets with object masks is extremely time consuming...
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Learning to Act Properly: Predicting and Explaining Affordances from Images
We address the problem of affordance reasoning in diverse scenes that ap...
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MovieGraphs: Towards Understanding Human-Centric Situations from Videos
There is growing interest in artificial intelligence to build socially i...
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Be Your Own Prada: Fashion Synthesis with Structural Coherence
We present a novel and effective approach for generating new clothing on...
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Situation Recognition with Graph Neural Networks
We address the problem of recognizing situations in images. Given an ima...
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VSE++: Improving Visual-Semantic Embeddings with Hard Negatives
We present a new technique for learning visual-semantic embeddings for c...
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Teaching Machines to Describe Images via Natural Language Feedback
Robots will eventually be part of every household. It is thus critical t...
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Open Vocabulary Scene Parsing
Recognizing arbitrary objects in the wild has been a challenging problem...
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