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researcher

Dequan Wang

University of California, Berkeley

19 papers hereh-index 188.5k citations42 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author6
  • middle author11

Across the 17 of 19 papers where every author was matched, so the position is known.

fields
  • cs.CV13
  • cs.LG2
  • cs.RO2
  • cs.AI1
  • eess.IV1
affiliations
  • University of California, Berkeley
Homepage
same name
  • Dequan Wang — 7 papers, h 9
  • Dequan Wang — 6 papers, h 3
  • Dequan Wang — 5 papers, h 1
  • Dequan Wang — 5 papers, h 3
  • Dequan Wang — 4 papers, h 2
  • Dequan Wang — 4 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162023
most citedFCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation

692 citations · 1.3k across the 10 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cs.CV2020★ 37 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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.