b'Adrien Gaidon'

research

∙ 05/22/2023

NeRFuser: Large-Scale Scene Representation by NeRF Fusion

A practical benefit of implicit visual representations like Neural Radia...

5 Jiading Fang, et al. ∙

research

∙ 04/06/2023

DeLiRa: Self-Supervised Depth, Light, and Radiance Fields

Differentiable volumetric rendering is a powerful paradigm for 3D recons...

4 Vitor Guizilini, et al. ∙

research

∙ 03/27/2023

Object Discovery from Motion-Guided Tokens

Object discovery – separating objects from the background without manual...

1 Zhipeng Bao, et al. ∙

research

∙ 03/25/2023

Viewpoint Equivariance for Multi-View 3D Object Detection

3D object detection from visual sensors is a cornerstone capability of r...

3 Dian Chen, et al. ∙

research

∙ 01/27/2023

In-Distribution Barrier Functions: Self-Supervised Policy Filters that Avoid Out-of-Distribution States

Learning-based control approaches have shown great promise in performing...

11 Fernando Castañeda, et al. ∙

research

∙ 12/12/2022

Breaking the "Object" in Video Object Segmentation

The appearance of an object can be fleeting when it transforms. As eggs ...

3 Pavel Tokmakov, et al. ∙

research

∙ 12/12/2022

ROAD: Learning an Implicit Recursive Octree Auto-Decoder to Efficiently Encode 3D Shapes

Compact and accurate representations of 3D shapes are central to many pe...

6 Sergey Zakharov, et al. ∙

research

∙ 10/23/2022

Photo-realistic Neural Domain Randomization

Synthetic data is a scalable alternative to manual supervision, but it r...

0 Sergey Zakharov, et al. ∙

research

∙ 10/05/2022

Depth Is All You Need for Monocular 3D Detection

A key contributor to recent progress in 3D detection from single images ...

8 Dennis Park, et al. ∙

research

∙ 10/04/2022

RAP: Risk-Aware Prediction for Robust Planning

Robust planning in interactive scenarios requires predicting the uncerta...

11 Haruki Nishimura, et al. ∙

research

∙ 07/28/2022

Depth Field Networks for Generalizable Multi-view Scene Representation

Modern 3D computer vision leverages learning to boost geometric reasonin...

6 Vitor Guizilini, et al. ∙

research

∙ 07/27/2022

ShAPO: Implicit Representations for Multi-Object Shape, Appearance, and Pose Optimization

Our method studies the complex task of object-centric 3D understanding f...

19 Muhammad Zubair Irshad, et al. ∙

research

∙ 07/22/2022

Seeing 3D Objects in a Single Image via Self-Supervised Static-Dynamic Disentanglement

Human perception reliably identifies movable and immovable parts of 3D s...

0 Prafull Sharma, et al. ∙

research

∙ 04/28/2022

Control-Aware Prediction Objectives for Autonomous Driving

Autonomous vehicle software is typically structured as a modular pipelin...

7 Rowan McAllister, et al. ∙

research

∙ 04/15/2022

Multi-Frame Self-Supervised Depth with Transformers

Multi-frame depth estimation improves over single-frame approaches by al...

2 Vitor Guizilini, et al. ∙

research

∙ 04/04/2022

Object Permanence Emerges in a Random Walk along Memory

This paper proposes a self-supervised objective for learning representat...

5 Pavel Tokmakov, et al. ∙

research

∙ 03/28/2022

Learning Optical Flow, Depth, and Scene Flow without Real-World Labels

Self-supervised monocular depth estimation enables robots to learn 3D pe...

13 Vitor Guizilini, et al. ∙

research

∙ 03/18/2022

Discovering Objects that Can Move

This paper studies the problem of object discovery – separating objects ...

13 Zhipeng Bao, et al. ∙

research

∙ 01/25/2022

Dynamics-Aware Comparison of Learned Reward Functions

The ability to learn reward functions plays an important role in enablin...

0 Blake Wulfe, et al. ∙

research

∙ 12/06/2021

Self-Supervised Camera Self-Calibration from Video

Camera calibration is integral to robotics and computer vision algorithm...

13 Jiading Fang, et al. ∙

research

∙ 10/11/2021

Self-supervised Learning is More Robust to Dataset Imbalance

Self-supervised learning (SSL) is a scalable way to learn general visual...

4 Hong Liu, et al. ∙

research

∙ 09/28/2021

Warp-Refine Propagation: Semi-Supervised Auto-labeling via Cycle-consistency

Deep learning models for semantic segmentation rely on expensive, large-...

4 Aditya Ganeshan, et al. ∙

research

∙ 08/13/2021

Is Pseudo-Lidar needed for Monocular 3D Object detection?

Recent progress in 3D object detection from single images leverages mono...

14 Dennis Park, et al. ∙

research

∙ 06/08/2021

Hierarchical Lovász Embeddings for Proposal-free Panoptic Segmentation

Panoptic segmentation brings together two separate tasks: instance and s...

6 Tommi Kerola, et al. ∙

research

∙ 06/08/2021

Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss

Recent works in self-supervised learning have advanced the state-of-the-...

2 Jeff Z. HaoChen, et al. ∙

research

∙ 04/26/2021

Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty

Reasoning about the future behavior of other agents is critical to safe ...

3 Boris Ivanovic, et al. ∙

research

∙ 03/31/2021

Full Surround Monodepth from Multiple Cameras

Self-supervised monocular depth and ego-motion estimation is a promising...

16 Vitor Guizilini, et al. ∙

research

∙ 03/30/2021

Geometric Unsupervised Domain Adaptation for Semantic Segmentation

Simulators can efficiently generate large amounts of labeled synthetic d...

18 Vitor Guizilini, et al. ∙

research

∙ 03/30/2021

Sparse Auxiliary Networks for Unified Monocular Depth Prediction and Completion

Estimating scene geometry from data obtained with cost-effective sensors...

7 Vitor Guizilini, et al. ∙

research

∙ 03/29/2021

Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark

The NeurIPS 2020 Procgen Competition was designed as a centralized bench...

26 Sharada Mohanty, et al. ∙

research

∙ 03/26/2021

Learning to Track with Object Permanence

Tracking by detection, the dominant approach for online multi-object tra...

7 Pavel Tokmakov, et al. ∙

research

∙ 01/05/2021

Monocular Depth Estimation for Soft Visuotactile Sensors

Fluid-filled soft visuotactile sensors such as the Soft-bubbles alleviat...

3 Rares Ambrus, et al. ∙

research

∙ 11/24/2020

Discovering Avoidable Planner Failures of Autonomous Vehicles using Counterfactual Analysis in Behaviorally Diverse Simulation

Automated Vehicles require exhaustive testing in simulation to detect as...

6 Daisuke Nishiyama, et al. ∙

research

∙ 11/11/2020

Behaviorally Diverse Traffic Simulation via Reinforcement Learning

Traffic simulators are important tools in autonomous driving development...

8 Shinya Shiroshita, et al. ∙

research

∙ 10/16/2020

RAT iLQR: A Risk Auto-Tuning Controller to Optimally Account for Stochastic Model Mismatch

Successful robotic operation in stochastic environments relies on accura...

0 Haruki Nishimura, et al. ∙

research

∙ 09/30/2020

Monocular Differentiable Rendering for Self-Supervised 3D Object Detection

3D object detection from monocular images is an ill-posed problem due to...

9 Deniz Beker, et al. ∙

research

∙ 09/16/2020

MATS: An Interpretable Trajectory Forecasting Representation for Planning and Control

Reasoning about human motion is a core component of modern human-robot i...

0 Boris Ivanovic, et al. ∙

research

∙ 09/12/2020

Risk-Sensitive Sequential Action Control with Multi-Modal Human Trajectory Forecasting for Safe Crowd-Robot Interaction

This paper presents a novel online framework for safe crowd-robot intera...

0 Haruki Nishimura, et al. ∙

research

∙ 08/29/2020

Driving Through Ghosts: Behavioral Cloning with False Positives

Safe autonomous driving requires robust detection of other traffic parti...

11 Andreas Bühler, et al. ∙

research

∙ 08/15/2020

Neural Ray Surfaces for Self-Supervised Learning of Depth and Ego-motion

Self-supervised learning has emerged as a powerful tool for depth and eg...

15 Igor Vasiljevic, et al. ∙

research

∙ 08/03/2020

PillarFlow: End-to-end Birds-eye-view Flow Estimation for Autonomous Driving

In autonomous driving, accurately estimating the state of surrounding ob...

4 Kuan-Hui Lee, et al. ∙

research

∙ 07/01/2020

Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving

Autonomous driving has achieved significant progress in recent years, bu...

7 Zhangjie Cao, et al. ∙

research

∙ 06/29/2020

Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization

Real-world large-scale datasets are heteroskedastic and imbalanced – lab...

1 Kaidi Cao, et al. ∙

research

∙ 06/22/2020

Differentiable Rendering: A Survey

Deep neural networks (DNNs) have shown remarkable performance improvemen...

22 Hiroharu Kato, et al. ∙

research

∙ 02/27/2020

Semantically-Guided Representation Learning for Self-Supervised Monocular Depth

Self-supervised learning is showing great promise for monocular depth es...

5 Vitor Guizilini, et al. ∙

research

∙ 12/07/2019

Self-Supervised 3D Keypoint Learning for Ego-motion Estimation

Generating reliable illumination and viewpoint invariant keypoints is cr...

0 Jiexiong Tang, et al. ∙

research

∙ 12/03/2019

Real-Time Panoptic Segmentation from Dense Detections

Panoptic segmentation is a complex full scene parsing task requiring sim...

0 Rui Hou, et al. ∙

research

∙ 11/26/2019

Autolabeling 3D Objects with Differentiable Rendering of SDF Shape Priors

We present an automatic annotation pipeline to recover 9D cuboids and 3D...

23 Sergey Zakharov, et al. ∙

research

∙ 11/04/2019

Disentangling Human Dynamics for Pedestrian Locomotion Forecasting with Noisy Supervision

We tackle the problem of Human Locomotion Forecasting, a task for jointl...

13 Karttikeya Mangalam, et al. ∙

research

∙ 10/12/2019

Generating Human Action Videos by Coupling 3D Game Engines and Probabilistic Graphical Models

Deep video action recognition models have been highly successful in rece...

26 César Roberto de Souza, et al. ∙

Adrien Gaidon

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