activity
20172022
most citedVisDA: The Visual Domain Adaptation Challenge

574 citations · 643 across the 6 of their papers we have counts for

collaborators

14 papers

cs.RO20224 cited

MAROAM: Map-based Radar SLAM through Two-step Feature Selection

Dequan Wang, Yifan Duan, Xiaoran Fan +3

In this letter, we propose MAROAM, a millimeter wave radar-based SLAM framework, which employs a two-step feature selection process to build the global consistent map. Specifically…

cs.CV202037 cited

BEV-Seg: Bird's Eye View Semantic Segmentation Using Geometry and Semantic Point Cloud

Mong H. Ng, Kaahan Radia, Jianfei Chen +3

Bird's-eye-view (BEV) is a powerful and widely adopted representation for road scenes that captures surrounding objects and their spatial locations, along with overall context in t…

cs.LG2020

Tent: Fully Test-time Adaptation by Entropy Minimization

Dequan Wang, Evan Shelhamer, Shaoteng Liu +2

A model must adapt itself to generalize to new and different data during testing. In this setting of fully test-time adaptation the model has only the test data and its own paramet…

cs.CV2020

CoDeNet: Efficient Deployment of Input-Adaptive Object Detection on Embedded FPGAs

Zhen Dong, Dequan Wang, Qijing Huang +6

Deploying deep learning models on embedded systems has been challenging due to limited computing resources. The majority of existing work focuses on accelerating image classificati…

eess.IV2020

Algorithm-hardware Co-design for Deformable Convolution

Qijing Huang, Dequan Wang, Yizhao Gao +5

FPGAs provide a flexible and efficient platform to accelerate rapidly-changing algorithms for computer vision. The majority of existing work focuses on accelerating image classific…

cs.CV2019

Dynamic Scale Inference by Entropy Minimization

Dequan Wang, Evan Shelhamer, Bruno Olshausen +1

Given the variety of the visual world there is not one true scale for recognition: objects may appear at drastically different sizes across the visual field. Rather than enumerate…