research
∙
09/18/2023
GEDepth: Ground Embedding for Monocular Depth Estimation
Monocular depth estimation is an ill-posed problem as the same 2D image ...
share
research
∙
06/12/2023
Transcendental Idealism of Planner: Evaluating Perception from Planning Perspective for Autonomous Driving
Evaluating the performance of perception modules in autonomous driving i...
research
∙
05/08/2023
PillarNeXt: Rethinking Network Designs for 3D Object Detection in LiDAR Point Clouds
In order to deal with the sparse and unstructured raw point clouds, LiDA...
research
∙
03/21/2023
ProphNet: Efficient Agent-Centric Motion Forecasting with Anchor-Informed Proposals
Motion forecasting is a key module in an autonomous driving system. Due ...
research
∙
11/14/2022
SportsTrack: An Innovative Method for Tracking Athletes in Sports Scenes
The SportsMOT competition aims to solve multiple object tracking of athl...
research
∙
07/13/2022
QML for Argoverse 2 Motion Forecasting Challenge
To safely navigate in various complex traffic scenarios, autonomous driv...
research
∙
06/27/2022
Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization
By ensuring differential privacy in the learning algorithms, one can rig...
research
∙
03/28/2022
TL-GAN: Improving Traffic Light Recognition via Data Synthesis for Autonomous Driving
Traffic light recognition, as a critical component of the perception mod...
research
∙
02/28/2022
Attribute Descent: Simulating Object-Centric Datasets on the Content Level and Beyond
This article aims to use graphic engines to simulate a large number of t...
research
∙
12/16/2021
On Gibbs Sampling for Structured Bayesian Models Discussion of paper by Zanella and Roberts
This article is a discussion of Zanella and Roberts' paper: Multilevel l...
research
∙
11/30/2021
Convergence Rate of Multiple-try Metropolis Independent sampler
The Multiple-try Metropolis (MTM) method is an interesting extension of ...
research
∙
11/16/2021
Learning Intrinsic Images for Clothing
Reconstruction of human clothing is an important task and often relies o...
research
∙
08/23/2021
Exploring Simple 3D Multi-Object Tracking for Autonomous Driving
3D multi-object tracking in LiDAR point clouds is a key ingredient for s...
research
∙
08/09/2021
Neural Network Repair with Reachability Analysis
Safety is a critical concern for the next generation of autonomy that is...
research
∙
06/22/2021
Reachability Analysis of Convolutional Neural Networks
Deep convolutional neural networks have been widely employed as an effec...
research
∙
04/18/2021
Self-Supervised Pillar Motion Learning for Autonomous Driving
Autonomous driving can benefit from motion behavior comprehension when i...
research
∙
10/21/2020
UFO^2: A Unified Framework towards Omni-supervised Object Detection
Existing work on object detection often relies on a single form of annot...
research
∙
07/20/2020
Hierarchical Contrastive Motion Learning for Video Action Recognition
One central question for video action recognition is how to model motion...
research
∙
07/20/2020
Joint Disentangling and Adaptation for Cross-Domain Person Re-Identification
Although a significant progress has been witnessed in supervised person ...
research
∙
06/17/2020
Contrastive Learning for Weakly Supervised Phrase Grounding
Phrase grounding, the problem of associating image regions to caption wo...
research
∙
05/02/2020
PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data
In comparison with person re-identification (ReID), which has been widel...
research
∙
04/30/2020
The 4th AI City Challenge
The AI City Challenge was created to accelerate intelligent video analys...
research
∙
04/26/2020
Reachable Set Estimation for Neural Network Control Systems: A Simulation-Guided Approach
The vulnerability of artificial intelligence (AI) and machine learning (...
research
∙
04/12/2020
NNV: The Neural Network Verification Tool for Deep Neural Networks and Learning-Enabled Cyber-Physical Systems
This paper presents the Neural Network Verification (NNV) software tool,...
research
∙
04/09/2020
Instance-aware, Context-focused, and Memory-efficient Weakly Supervised Object Detection
Weakly supervised learning has emerged as a compelling tool for object d...
research
∙
03/02/2020
Reachability Analysis for Feed-Forward Neural Networks using Face Lattices
Deep neural networks have been widely applied as an effective approach t...
research
∙
01/29/2020
FOCUS: Dealing with Label Quality Disparity in Federated Learning
Ubiquitous systems with End-Edge-Cloud architecture are increasingly bei...
research
∙
12/18/2019
Simulating Content Consistent Vehicle Datasets with Attribute Descent
We simulate data using a graphic engine to augment real-world datasets, ...
research
∙
11/05/2019
Dancing to Music
Dancing to music is an instinctive move by humans. Learning to model the...
research
∙
08/18/2019
A Delay Metric for Video Object Detection: What Average Precision Fails to Tell
Average precision (AP) is a widely used metric to evaluate detection acc...
research
∙
05/29/2019
Rethinking Full Connectivity in Recurrent Neural Networks
Recurrent neural networks (RNNs) are omnipresent in sequence modeling ta...
research
∙
04/19/2019
STEP: Spatio-Temporal Progressive Learning for Video Action Detection
In this paper, we propose Spatio-TEmporal Progressive (STEP) action dete...
research
∙
04/15/2019
Joint Discriminative and Generative Learning for Person Re-identification
Person re-identification (re-id) remains challenging due to significant ...
research
∙
03/21/2019
CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification
Urban traffic optimization using traffic cameras as sensors is driving t...
research
∙
02/12/2019
QoS-Aware Buffer-Aided Relaying Implant WBAN for Healthcare IoT: Opportunities and Challenges
Internet of Things (IoT) have motivated a paradigm shift in the developm...
research
∙
11/29/2018
Discovering Spatio-Temporal Action Tubes
In this paper, we address the challenging problem of spatial and tempora...
research
∙
10/03/2018
Verification for Machine Learning, Autonomy, and Neural Networks Survey
This survey presents an overview of verification techniques for autonomo...
research
∙
09/14/2018
Models Matter, So Does Training: An Empirical Study of CNNs for Optical Flow Estimation
We investigate two crucial and closely related aspects of CNNs for optic...
research
∙
11/30/2017
Budget-Aware Activity Detection with A Recurrent Policy Network
In this paper, we address the challenging problem of effi- cient tempora...
research
∙
09/07/2017
PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume
We present a compact but effective CNN model for optical flow, called PW...
research
∙
07/17/2017
