Monocular Depth Estimation - Unsupervised
DrivingStereo: A Large-Scale Dataset for Stereo Matching in Autonomous Driving Scenarios
A Dataset and Explorer for 3D Signed Distance Functions
Fourier Neural Operator for Parametric Partial Differential Equations
Neural Ordinary Differential Equations
Latent ODEs for Irregularly-Sampled Time Series
Lie Groups for 2D and 3D Transformations
Sparsely Annotated Object Detection: A Region-based Semi-supervised Approach
GraftNet: Towards Domain Generalized Stereo Matching with a Broad-Spectrum and Task-Oriented Feature
RAFT-Stereo: Multilevel Recurrent Field Transforms for Stereo Matching
Attention-Aware Feature Aggregation for Real-time Stereo Matching on Edge Devices
HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matching
Deep Learning Stereo Vision at the edge
Differentiable Signed Distance Function Rendering
NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Video
Atlas: End-to-End 3D Scene Reconstruction from Posed Images
3D Semantic Scene Completion: a Survey
SG-NN: Sparse Generative Neural Networks for Self-Supervised Scene Completion of RGB-D Scans
Truncated Signed Distance Fields applied to robotics
DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes
A Volumetric Method for Building Complex Models from Range Images
KinectFusion: Real-Time Dense Surface Mapping and Tracking
Signed Distance Fields: A Natural Representation for Both Mapping and Planning
Spatial Imagination With Semantic Cognition for Mobile Robots
Controllable and Progressive Image Extrapolation
BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Models
Multi-Object Tracking with Hallucinated and Unlabeled Videos
TAP-Vid: A Benchmark for Tracking Any Point in a Video
The Sensory Neuron as a Transformer: Permutation-Invariant Neural Networks for RL
DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames
Transformers are Sample Efficient World Models
The 37 Implementation Details of Proximal Policy Optimization
Mastering Atari Games with Limited Data
QUANTIFYING DIFFERENCES IN REWARD FUNCTIONS
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning
Dream to Control: Learning Behaviors by Latent Imagination
Mastering Atari with Discrete World Models
Learning Invariant Representations for Reinforcement Learning without Reconstruction
Discrete Latent Space World Models for Reinforcement Learning World model based on vector quantized variational autoencoder (VQ-VAE)
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
SOFT ACTOR-CRITIC FOR DISCRETE ACTION SETTINGS
Proximal Policy Optimization Algorithms
High-Dimensional Continuous Control Using Generalized Advantage Estimation (Advantage)
Asynchronous Methods for Deep Reinforcement Learning
Trust Region Policy Optimization
Deep Reinforcement Learning for Imperfect-Information Games
Playing Atari with Deep Reinforcement Learning (Replay buffer)
Meta-SAC: Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient
Meta-Gradient Reinforcement Learning
REALM: Retrieval-Augmented Language Model Pre-Training
Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning
Recursively Summarizing Books with Human Feedback
Code as Policies: Language Model Programs for Embodied Control
IS CONDITIONAL GENERATIVE MODELING ALL YOU NEED FOR DECISION-MAKING?
SAMPLE-EFFICIENT REINFORCEMENT LEARNING BY BREAKING THE REPLAY RATIO BARRIER
Is Conditional Generative Modeling all you need for Decision-Making?
Know Your Boundaries: The Necessity of Explicit Behavioral Cloning in Offline RL
A Pragmatic Look at Deep Imitation Learning
A DATASET PERSPECTIVE ON OFFLINE REINFORCEMENT LEARNING
General Policy Evaluation and Improvement by Learning to Identify Few But Crucial States
Contrastive Learning as Goal-Conditioned Reinforcement Learning
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Behavior Transformers: Cloning k modes with one stone
A Minimalist Approach to Offline Reinforcement Learning
Conservative Q-Learning for Offline Reinforcement Learning
Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning
Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning
Online and Offline Reinforcement Learning by Planning with a Learned Model
Regularized Behavior Value Estimation
Accelerating Online Reinforcement Learning with Offline Datasets
Off-Policy Evaluation via Off-Policy Classification
Learning One Representation to Optimize All Rewards
Generalized State-Dependent Exploration for Deep Reinforcement Learning in Robotics
Is Out-of-Distribution Detection Learnable?
Learning to Control PDEs with Differentiable Physics
DiffTaichi: Differentiable Programming for Physical Simulation
End-to-End Differentiable Physics for Learning and Control
ADD: Analytically Differentiable Dynamics for Multi-Body Systems with Frictional Contact
LEARNING MESH-BASED SIMULATION WITH GRAPH NETWORKS
Learning mesh-based simulation with graph networks
Sequential Dexterity: Chaining Dexterous Policies for Long-Horizon Manipulation
DEP-RL:EMBODIEDEXPLORATIONFOR REINFORCEMENTLEARNINGIN OVERACTUATEDANDMUSCULOSKELETALSYSTEMS
An Active Learning Based Robot Kinematic Calibration Framework Using Gaussian Processes
RMA: Rapid Motor Adaptation for Legged Robots
Transporter Networks: Rearranging the Visual World for Robotic Manipulation
A micro Lie theory for state estimation in robotics
Reinforcement Learning with Videos: Combining Offline Observations with Interaction
Contingencies from Observations: Tractable ContingencyPlanning with Learned Behavior Models
DeepGait: Planning and Control of Quadrupedal Gaits using Deep Reinforcement Learning
Closing the Sim-To-Real Gap with Evolutionary Meta-Learning
Deep occupancy maps: a continuous mapping technique for dynamic environments
Multi-Object Search using Object-Oriented POMDPs
Multi-Resolution POMDP Planning for Multi-Object Search in 3D
Practical and Optimal LSH for Angular Distance
DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras
RAFT: Recurrent All-Pairs Field Transforms for Optical Flow
CeMNet: Self-supervised learning for accurate continuous ego-motion estimation
HIGH SPEED NONHOLONOMIC MOBILE ROBOT ONLINE TRAJECTORY OPTIMATIZATION
RANSAC Matching: Simultaneous Registration and Segmentation
Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation Paper Explained
Form2Fit: Learning Shape Priors for Generalizable Assembly
TossingBot: Learning to Throw Arbitrary Objects with Residual Physics
Solving Rubik's Cube with a Robot Hand
Learning Dexterous In-Hand Manipulation
Beyond English-Centric Multilingual Machine Translation
Parallel Context Windows Improve In-Context Learning of Large Language Models
Scaling Transformer to 1M tokens and beyond with RMT
Encoding Recurrence into Transformers
Gradient Estimation with Discrete Stein Operators
What Makes Convolutional Models Great on Long Sequence Modeling?
CFPNet-Medicine <-- fast U-net
DeepNet: Scaling Transformers to 1,000 Layers
Autoregressive Diffusion Models
Geometric Deep Learning Grids, Groups, Graphs,Geodesics, and Gauges
DATASET CONDENSATION WITH GRADIENT MATCHING
Learning to Learn Single Domain Generalization
DEUP: Direct Epistemic Uncertainty Prediction
Solving Mixed Integer Programs Using Neural Networks
High Quality Monocular Depth Estimation via Transfer Learning
RETHINKING ATTENTION WITH PERFORMERS
NEURAL OBLIVIOUS DECISION ENSEMBLES FOR DEEP LEARNING ON TABULAR DATA
One-shot conditional audio filtering of arbitrary sounds
Soft Rasterizer: A Differentiable Renderer for Image-based 3D Reasoning
Fully Convolutional Instance-aware Semantic Segmentation
Feature Pyramid Networks for Object Detection
Transformers in vision: A survey
LAMBDANETWORKS: MODELING LONG-RANGE INTERACTIONS WITHOUT ATTENTION code
In Defense of Grid Features for Visual Question Answering
Adversarially Robust Generalization Requires More Data
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data
Large-Batch Training for LSTM and Beyond
RandAugment: Practical automated data augmentation with a reduced search space
https://arxiv.org/abs/2010.11929
A Cookbook of Self-Supervised Learning
Adversarial Masking for Self-Supervised Learning
MoFA: Model-based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstruction
Motion Representations for Articulated Animation
DINO: Emerging Properties in Self-Supervised Vision Transformers
Theory and Experiments on Vector Quantized Autoencoders
Learning deep representations by mutual information estimation and maximization
Unsupervised Learning of Object Keypoints for Perception and Control
Unsupervised Learning of Object Landmarks through Conditional Image Generation
Implicit 3D Orientation Learning for 6D Object Detection from RGB Images
Efficient Training for Positive Unlabeled Learning
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Scaling and Benchmarking Self-Supervised Visual Representation Learning
Invariant Information Clustering for Unsupervised Image Classification and Segmentation
A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions
DARTS: DIFFERENTIABLE ARCHITECTURE SEARCH
OOD-MAML: Meta-Learning for Few-Shot Out-of-Distribution Detection and Classification