b'Dengxin Dai'

research

∙ 07/24/2023

LiDAR Meta Depth Completion

Depth estimation is one of the essential tasks to be addressed when crea...

0 Wolfgang Boettcher, et al. ∙

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...

0 Shaoshuai Shi, et al. ∙

research

∙ 05/22/2023

HGFormer: Hierarchical Grouping Transformer for Domain Generalized Semantic Segmentation

Current semantic segmentation models have achieved great success under t...

0 Jian Ding, et al. ∙

research

∙ 05/11/2023

FreePoint: Unsupervised Point Cloud Instance Segmentation

Instance segmentation of point clouds is a crucial task in 3D field with...

0 Zhikai Zhang, et al. ∙

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...

0 Li Jiang, et al. ∙

research

∙ 04/27/2023

EDAPS: Enhanced Domain-Adaptive Panoptic Segmentation

With autonomous industries on the rise, domain adaptation of the visual ...

0 Suman Saha, et al. ∙

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...

0 Lukas Hoyer, et al. ∙

research

∙ 04/10/2023

Federated Incremental Semantic Segmentation

Federated learning-based semantic segmentation (FSS) has drawn widesprea...

0 Jiahua Dong, et al. ∙

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...

0 Zhejun Zhang, et al. ∙

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...

0 Jiahua Dong, et al. ∙

research

∙ 01/03/2023

Benchmarking the Robustness of LiDAR Semantic Segmentation Models

When using LiDAR semantic segmentation models for safety-critical applic...

0 Xu Yan, et al. ∙

research

∙ 12/16/2022

Simulating Road Spray Effects in Automotive Lidar Sensor Models

Modeling perception sensors is key for simulation based testing of autom...

0 Clemens Linnhoff, et al. ∙

research

∙ 12/02/2022

MIC: Masked Image Consistency for Context-Enhanced Domain Adaptation

In unsupervised domain adaptation (UDA), a model trained on source data ...

0 Lukas Hoyer, et al. ∙

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...

0 Qi Fan, et al. ∙

research

∙ 09/27/2022

Motion Transformer with Global Intention Localization and Local Movement Refinement

Predicting multimodal future behavior of traffic participants is essenti...

0 Shaoshuai Shi, et al. ∙

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 ...

0 Shaoshuai Shi, et al. ∙

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...

0 Yu-Huan Wu, et al. ∙

research

∙ 06/30/2022

HRFuser: A Multi-resolution Sensor Fusion Architecture for 2D Object Detection

Besides standard cameras, autonomous vehicles typically include multiple...

0 Tim Broedermann, et al. ∙

research

∙ 05/25/2022

Deep Gradient Learning for Efficient Camouflaged Object Detection

This paper introduces DGNet, a novel deep framework that exploits object...

0 Ge-Peng Ji, et al. ∙

research

∙ 05/12/2022

Bi-level Alignment for Cross-Domain Crowd Counting

Recently, crowd density estimation has received increasing attention. Th...

0 Shenjian Gong, et al. ∙

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...

8 Lukas Hoyer, et al. ∙

research

∙ 03/28/2022

LiDAR Snowfall Simulation for Robust 3D Object Detection

3D object detection is a central task for applications such as autonomou...

0 Martin Hahner, et al. ∙

research

∙ 03/16/2022

Scribble-Supervised LiDAR Semantic Segmentation

Densely annotating LiDAR point clouds remains too expensive and time-con...

0 Ozan Unal, et al. ∙

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...

0 Shengqu Cai, et al. ∙

research

∙ 02/17/2022

Adiabatic Quantum Computing for Multi Object Tracking

Multi-Object Tracking (MOT) is most often approached in the tracking-by-...

16 Jan-Nico Zaech, et al. ∙

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...

10 Niclas Vödisch, et al. ∙

research

∙ 01/04/2022

Sound and Visual Representation Learning with Multiple Pretraining Tasks

Different self-supervised tasks (SSL) reveal different features from the...

0 Arun Balajee Vasudevan, et al. ∙

research

∙ 12/15/2021

Decoupling Zero-Shot Semantic Segmentation

Zero-shot semantic segmentation (ZS3) aims to segment the novel categori...

9 Jian Ding, et al. ∙

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...

0 Yue Fan, et al. ∙

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...

0 Xianzheng Ma, et al. ∙

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...

20 Lukas Hoyer, et al. ∙

research

∙ 09/10/2021

TADA: Taxonomy Adaptive Domain Adaptation

Traditional domain adaptation addresses the task of adapting a model to ...

0 Rui Gong, et al. ∙

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...

0 Dengxin Dai, et al. ∙

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...

0 Zhejun Zhang, et al. ∙

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...

7 Martin Hahner, et al. ∙

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...

0 Christos Sakaridis, et al. ∙

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 ...

0 Jan-Nico Zaech, et al. ∙

research

∙ 03/07/2021

Spectral Tensor Train Parameterization of Deep Learning Layers

We study low-rank parameterizations of weight matrices with embedded spe...

15 Anton Obukhov, et al. ∙

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...

17 Ke Li, et al. ∙

research

∙ 12/19/2020

Three Ways to Improve Semantic Segmentation with Self-Supervised Depth Estimation

Training deep networks for semantic segmentation requires large amounts ...

9 Lukas Hoyer, et al. ∙

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...

0 Rui Gong, et al. ∙

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...

0 Rui Gong, et al. ∙

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...

2 Juan-Ting Lin, et al. ∙

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 ...

2 Ozan Unal, et al. ∙

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...

10 Qinghao Meng, et al. ∙

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...

29 Yuan Tian, et al. ∙

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 ...

20 Anton Obukhov, et al. ∙

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...

0 Simon Hecker, et al. ∙

research

∙ 06/28/2020

Analogical Image Translation for Fog Generation

Image-to-image translation is to map images from a given style to anothe...

0 Rui Gong, et al. ∙

research

∙ 05/28/2020

Map-Guided Curriculum Domain Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation

We address the problem of semantic nighttime image segmentation and impr...

3 Christos Sakaridis, et al. ∙

Dengxin Dai

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