b'Dengxin Dai'

research

∙ 06/30/2022

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

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

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...

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...

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...

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...

Martin Hahner, et al. ∙

research

∙ 03/16/2022

Scribble-Supervised LiDAR Semantic Segmentation

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

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...

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-...

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...

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...

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...

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...

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...

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...

Lukas Hoyer, et al. ∙

research

∙ 09/10/2021

TADA: Taxonomy Adaptive Domain Adaptation

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

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...

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...

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...

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...

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 ...

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...

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...

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 ...

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...

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...

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...

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 ...

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...

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...

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 ...

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...

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...

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...

Christos Sakaridis, et al. ∙

research

∙ 04/29/2020

Action Sequence Predictions of Vehicles in Urban Environments using Map and Social Context

This work studies the problem of predicting the sequence of future actio...

Jan-Nico Zaech, et al. ∙

research

∙ 04/28/2020

Revisiting Multi-Task Learning in the Deep Learning Era

Despite the recent progress in deep learning, most approaches still go f...

Simon Vandenhende, et al. ∙

research

∙ 04/03/2020

Quantifying Data Augmentation for LiDAR based 3D Object Detection

In this work, we shed light on different data augmentation techniques co...

Martin Hahner, et al. ∙

research

∙ 03/09/2020

Semantic Object Prediction and Spatial Sound Super-Resolution with Binaural Sounds

Humans can robustly recognize and localize objects by integrating visual...

Arun Balajee Vasudevan, et al. ∙

research

∙ 03/02/2020

Matching Neuromorphic Events and Color Images via Adversarial Learning

The event camera has appealing properties: high dynamic range, low laten...

Fang Xu, et al. ∙

research

∙ 01/08/2020

Don't Forget The Past: Recurrent Depth Estimation from Monocular Video

Autonomous cars need continuously updated depth information. Thus far, t...

Vaishakh Patil, et al. ∙

research

∙ 12/09/2019

Self-supervised Object Motion and Depth Estimation from Video

We present a self-supervised learning framework to estimate the individu...

Qi Dai, et al. ∙

research

∙ 10/09/2019

Semantic Understanding of Foggy Scenes with Purely Synthetic Data

This work addresses the problem of semantic scene understanding under fo...

Martin Hahner, et al. ∙

research

∙ 10/04/2019

Talk2Nav: Long-Range Vision-and-Language Navigation in Cities

Autonomous driving models often consider the goal as fixed at the start ...

Arun Balajee Vasudevan, et al. ∙

research

∙ 08/29/2019

Texture Underfitting for Domain Adaptation

Comprehensive semantic segmentation is one of the key components for rob...

Jan-Nico Zaech, et al. ∙

research

∙ 07/12/2019

Learning a Curve Guardian for Motorcycles

Up to 17 through a curve and the main cause of curve accidents can be at...

Simon Hecker, et al. ∙

research

∙ 06/11/2019

Gated CRF Loss for Weakly Supervised Semantic Image Segmentation

State-of-the-art approaches for semantic segmentation rely on deep convo...

Anton Obukhov, et al. ∙

research

∙ 03/26/2019

Learning Accurate, Comfortable and Human-like Driving

Autonomous vehicles are more likely to be accepted if they drive accurat...

Simon Hecker, et al. ∙

research

∙ 02/06/2019

Real-time 3D Traffic Cone Detection for Autonomous Driving

Considerable progress has been made in semantic scene understanding of r...

Ankit Dhall, et al. ∙

research

∙ 01/17/2019

Semantic Nighttime Image Segmentation with Synthetic Stylized Data, Gradual Adaptation and Uncertainty-Aware Evaluation

This work addresses the problem of semantic segmentation of nighttime im...

Christos Sakaridis, et al. ∙

research

∙ 01/05/2019

Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene Understanding

This work addresses the problem of semantic scene understanding under fo...

Dengxin Dai, et al. ∙

research

∙ 10/05/2018

Dark Model Adaptation: Semantic Image Segmentation from Daytime to Nighttime

This work addresses the problem of semantic image segmentation of nightt...

Dengxin Dai, et al. ∙

Dengxin Dai

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