research
∙
07/24/2023
LiDAR Meta Depth Completion
Depth estimation is one of the essential tasks to be addressed when crea...
share
research
∙
06/30/2023
MTR++: Multi-Agent Motion Prediction with Symmetric Scene Modeling and Guided Intention Querying
Motion prediction is crucial for autonomous driving systems to understan...
research
∙
05/22/2023
HGFormer: Hierarchical Grouping Transformer for Domain Generalized Semantic Segmentation
Current semantic segmentation models have achieved great success under t...
research
∙
05/11/2023
FreePoint: Unsupervised Point Cloud Instance Segmentation
Instance segmentation of point clouds is a crucial task in 3D field with...
research
∙
05/08/2023
Self-supervised Pre-training with Masked Shape Prediction for 3D Scene Understanding
Masked signal modeling has greatly advanced self-supervised pre-training...
research
∙
04/27/2023
EDAPS: Enhanced Domain-Adaptive Panoptic Segmentation
With autonomous industries on the rise, domain adaptation of the visual ...
research
∙
04/26/2023
Domain Adaptive and Generalizable Network Architectures and Training Strategies for Semantic Image Segmentation
Unsupervised domain adaptation (UDA) and domain generalization (DG) enab...
research
∙
04/10/2023
Federated Incremental Semantic Segmentation
Federated learning-based semantic segmentation (FSS) has drawn widesprea...
research
∙
03/07/2023
TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction
Data-driven simulation has become a favorable way to train and test auto...
research
∙
02/02/2023
No One Left Behind: Real-World Federated Class-Incremental Learning
Federated learning (FL) is a hot collaborative training framework via ag...
research
∙
01/03/2023
Benchmarking the Robustness of LiDAR Semantic Segmentation Models
When using LiDAR semantic segmentation models for safety-critical applic...
research
∙
12/16/2022
Simulating Road Spray Effects in Automotive Lidar Sensor Models
Modeling perception sensors is key for simulation based testing of autom...
research
∙
12/02/2022
MIC: Masked Image Consistency for Context-Enhanced Domain Adaptation
In unsupervised domain adaptation (UDA), a model trained on source data ...
research
∙
11/08/2022
Normalization Perturbation: A Simple Domain Generalization Method for Real-World Domain Shifts
Improving model's generalizability against domain shifts is crucial, esp...
research
∙
09/27/2022
Motion Transformer with Global Intention Localization and Local Movement Refinement
Predicting multimodal future behavior of traffic participants is essenti...
research
∙
09/20/2022
MTR-A: 1st Place Solution for 2022 Waymo Open Dataset Challenge – Motion Prediction
In this report, we present the 1st place solution for motion prediction ...
research
∙
08/18/2022
Ret3D: Rethinking Object Relations for Efficient 3D Object Detection in Driving Scenes
Current efficient LiDAR-based detection frameworks are lacking in exploi...
research
∙
06/30/2022
HRFuser: A Multi-resolution Sensor Fusion Architecture for 2D Object Detection
Besides standard cameras, autonomous vehicles typically include multiple...
research
∙
05/25/2022
Deep Gradient Learning for Efficient Camouflaged Object Detection
This paper introduces DGNet, a novel deep framework that exploits object...
research
∙
05/12/2022
Bi-level Alignment for Cross-Domain Crowd Counting
Recently, crowd density estimation has received increasing attention. Th...
research
∙
04/27/2022
HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation
Unsupervised domain adaptation (UDA) aims to adapt a model trained on th...
research
∙
03/28/2022
LiDAR Snowfall Simulation for Robust 3D Object Detection
3D object detection is a central task for applications such as autonomou...
research
∙
03/16/2022
Scribble-Supervised LiDAR Semantic Segmentation
Densely annotating LiDAR point clouds remains too expensive and time-con...
research
∙
02/26/2022
Pix2NeRF: Unsupervised Conditional π-GAN for Single Image to Neural Radiance Fields Translation
We propose a pipeline to generate Neural Radiance Fields (NeRF) of an ob...
research
∙
02/17/2022
Adiabatic Quantum Computing for Multi Object Tracking
Multi-Object Tracking (MOT) is most often approached in the tracking-by-...
research
∙
01/11/2022
End-To-End Optimization of LiDAR Beam Configuration for 3D Object Detection and Localization
Existing learning methods for LiDAR-based applications use 3D points sca...
research
∙
01/04/2022
Sound and Visual Representation Learning with Multiple Pretraining Tasks
Different self-supervised tasks (SSL) reveal different features from the...
research
∙
12/15/2021
Decoupling Zero-Shot Semantic Segmentation
Zero-shot semantic segmentation (ZS3) aims to segment the novel categori...
research
∙
12/08/2021
CoSSL: Co-Learning of Representation and Classifier for Imbalanced Semi-Supervised Learning
In this paper, we propose a novel co-learning framework (CoSSL) with dec...
research
∙
12/01/2021
Both Style and Fog Matter: Cumulative Domain Adaptation for Semantic Foggy Scene Understanding
Although considerable progress has been made in semantic scene understan...
research
∙
11/29/2021
DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation
As acquiring pixel-wise annotations of real-world images for semantic se...
research
∙
09/10/2021
TADA: Taxonomy Adaptive Domain Adaptation
Traditional domain adaptation addresses the task of adapting a model to ...
research
∙
09/06/2021
Binaural SoundNet: Predicting Semantics, Depth and Motion with Binaural Sounds
Humans can robustly recognize and localize objects by using visual and/o...
research
∙
08/18/2021
End-to-End Urban Driving by Imitating a Reinforcement Learning Coach
End-to-end approaches to autonomous driving commonly rely on expert demo...
research
∙
08/11/2021
Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse Weather
This work addresses the challenging task of LiDAR-based 3D object detect...
research
∙
04/27/2021
ACDC: The Adverse Conditions Dataset with Correspondences for Semantic Driving Scene Understanding
Level 5 autonomy for self-driving cars requires a robust visual percepti...
research
∙
04/23/2021
Learnable Online Graph Representations for 3D Multi-Object Tracking
Tracking of objects in 3D is a fundamental task in computer vision that ...
research
∙
03/07/2021
Spectral Tensor Train Parameterization of Deep Learning Layers
We study low-rank parameterizations of weight matrices with embedded spe...
research
∙
01/19/2021
Hyperspectral Image Super-Resolution with Spectral Mixup and Heterogeneous Datasets
This work studies Hyperspectral image (HSI) super-resolution (SR). HSI S...
research
∙
12/19/2020
Three Ways to Improve Semantic Segmentation with Self-Supervised Depth Estimation
Training deep networks for semantic segmentation requires large amounts ...
research
∙
12/15/2020
mDALU: Multi-Source Domain Adaptation and Label Unification with Partial Datasets
Object recognition advances very rapidly these days. One challenge is to...
research
∙
12/15/2020
Cluster, Split, Fuse, and Update: Meta-Learning for Open Compound Domain Adaptive Semantic Segmentation
Open compound domain adaptation (OCDA) is a domain adaptation setting, w...
research
∙
09/30/2020
Depth Estimation from Monocular Images and Sparse Radar Data
In this paper, we explore the possibility of achieving a more accurate d...
research
∙
09/22/2020
Improving Point Cloud Semantic Segmentation by Learning 3D Object Proposal Generation
Point cloud semantic segmentation plays an essential role in autonomous ...
research
∙
07/23/2020
Weakly Supervised 3D Object Detection from Lidar Point Cloud
It is laborious to manually label point cloud data for training high-qua...
research
∙
07/17/2020
Off-Policy Reinforcement Learning for Efficient and Effective GAN Architecture Search
In this paper, we introduce a new reinforcement learning (RL) based neur...
research
∙
07/13/2020
T-Basis: a Compact Representation for Neural Networks
We introduce T-Basis, a novel concept for a compact representation of a ...
research
∙
07/10/2020
Learning Accurate and Human-Like Driving using Semantic Maps and Attention
This paper investigates how end-to-end driving models can be improved to...
research
∙
06/28/2020
Analogical Image Translation for Fog Generation
Image-to-image translation is to map images from a given style to anothe...
research
∙
05/28/2020
