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Dequan Wang
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2020 – today
- 2024
- [j4]Dequan Wang, Xinran Zhang, Kai Wang, Lingyu Wang, Xiaoran Fan, Yanyong Zhang:
RDGait: A mmWave Based Gait User Recognition System for Complex Indoor Environments Using Single-chip Radar. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 8(3): 134:1-134:31 (2024) - [j3]Chengzhen Meng, Yifan Duan, Chenming He, Dequan Wang, Xiaoran Fan, Yanyong Zhang:
mmPlace: Robust Place Recognition With Intermediate Frequency Signal of Low-Cost Single-Chip Millimeter Wave Radar. IEEE Robotics Autom. Lett. 9(6): 4878-4885 (2024) - [c22]Jin Gao, Lei Gan, Yuankai Li, Yixin Ye, Dequan Wang:
Dissecting Dissonance: Benchmarking Large Multimodal Models Against Self-Contradictory Instructions. ECCV (57) 2024: 404-420 - [c21]Siqi Kou, Lei Gan, Dequan Wang, Chongxuan Li, Zhijie Deng:
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference. ICLR 2024 - [c20]Yifan Lu, Yue Hu, Yiqi Zhong, Dequan Wang, Yanfeng Wang, Siheng Chen:
An Extensible Framework for Open Heterogeneous Collaborative Perception. ICLR 2024 - [i36]Yunkun Zhang, Jin Gao, Zheling Tan, Lingfeng Zhou, Kexin Ding, Mu Zhou, Shaoting Zhang, Dequan Wang:
Data-Centric Foundation Models in Computational Healthcare: A Survey. CoRR abs/2401.02458 (2024) - [i35]Yifan Lu, Yue Hu, Yiqi Zhong, Dequan Wang, Siheng Chen, Yanfeng Wang:
An Extensible Framework for Open Heterogeneous Collaborative Perception. CoRR abs/2401.13964 (2024) - [i34]Xiaosong Wang, Xiaofan Zhang, Guotai Wang, Junjun He, Zhongyu Li, Wentao Zhu, Yi Guo, Qi Dou, Xiaoxiao Li, Dequan Wang, Liang Hong, Qicheng Lao, Tong Ruan, Yukun Zhou, Yixue Li, Jie Zhao, Kang Li, Xin Sun, Lifeng Zhu, Shaoting Zhang:
OpenMEDLab: An Open-source Platform for Multi-modality Foundation Models in Medicine. CoRR abs/2402.18028 (2024) - [i33]Chengzhen Meng, Yifan Duan, Chenming He, Dequan Wang, Xiaoran Fan, Yanyong Zhang:
mmPlace: Robust Place Recognition with Intermediate Frequency Signal of Low-cost Single-chip Millimeter Wave Radar. CoRR abs/2403.04703 (2024) - [i32]Yixing Li, Yuxian Gu, Li Dong, Dequan Wang, Yu Cheng, Furu Wei:
Direct Preference Knowledge Distillation for Large Language Models. CoRR abs/2406.19774 (2024) - [i31]Juntu Zhao, Junyu Deng, Yixin Ye, Chongxuan Li, Zhijie Deng, Dequan Wang:
Lost in Translation: Latent Concept Misalignment in Text-to-Image Diffusion Models. CoRR abs/2408.00230 (2024) - [i30]Jin Gao, Lei Gan, Yuankai Li, Yixin Ye, Dequan Wang:
Dissecting Dissonance: Benchmarking Large Multimodal Models Against Self-Contradictory Instructions. CoRR abs/2408.01091 (2024) - [i29]Zhenyu Wang, Yi Xu, Dequan Wang, Lingfeng Zhou, Yiqi Zhou:
Intelligent Computing Social Modeling and Methodological Innovations in Political Science in the Era of Large Language Models. CoRR abs/2410.16301 (2024) - 2023
- [c19]Jin Gao, Jialing Zhang, Xihui Liu, Trevor Darrell, Evan Shelhamer, Dequan Wang:
Back to the Source: Diffusion-Driven Adaptation to Test-Time Corruption. CVPR 2023: 11786-11796 - [c18]Yunkun Zhang, Jin Gao, Mu Zhou, Xiaosong Wang, Yu Qiao, Shaoting Zhang, Dequan Wang:
Text-Guided Foundation Model Adaptation for Pathological Image Classification. MICCAI (5) 2023: 272-282 - [i28]Huahui Yi, Ziyuan Qin, Qicheng Lao, Wei Xu, Zekun Jiang, Dequan Wang, Shaoting Zhang, Kang Li:
Towards General Purpose Medical AI: Continual Learning Medical Foundation Model. CoRR abs/2303.06580 (2023) - [i27]Dequan Wang, Xiaosong Wang, Lilong Wang, Mengzhang Li, Qian Da, Xiaoqiang Liu, Xiangyu Gao, Jun Shen, Junjun He, Tian Shen, Qi Duan, Jie Zhao, Kang Li, Yu Qiao, Shaoting Zhang:
MedFMC: A Real-world Dataset and Benchmark For Foundation Model Adaptation in Medical Image Classification. CoRR abs/2306.09579 (2023) - [i26]Yunkun Zhang, Jin Gao, Mu Zhou, Xiaosong Wang, Yu Qiao, Shaoting Zhang, Dequan Wang:
Text-guided Foundation Model Adaptation for Pathological Image Classification. CoRR abs/2307.14901 (2023) - [i25]Siqi Kou, Lei Gan, Dequan Wang, Chongxuan Li, Zhijie Deng:
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference. CoRR abs/2310.11142 (2023) - 2022
- [c17]Dian Chen, Dequan Wang, Trevor Darrell, Sayna Ebrahimi:
Contrastive Test-Time Adaptation. CVPR 2022: 295-305 - [c16]Xiaoxuan Liu, Lianmin Zheng, Dequan Wang, Yukuo Cen, Weize Chen, Xu Han, Jianfei Chen, Zhiyuan Liu, Jie Tang, Joey Gonzalez, Michael W. Mahoney, Alvin Cheung:
GACT: Activation Compressed Training for Generic Network Architectures. ICML 2022: 14139-14152 - [i24]Dian Chen, Dequan Wang, Trevor Darrell, Sayna Ebrahimi:
Contrastive Test-Time Adaptation. CoRR abs/2204.10377 (2022) - [i23]Xiaoxuan Liu, Lianmin Zheng, Dequan Wang, Yukuo Cen, Weize Chen, Xu Han, Jianfei Chen, Zhiyuan Liu, Jie Tang, Joey Gonzalez, Michael W. Mahoney, Alvin Cheung:
GACT: Activation Compressed Training for General Architectures. CoRR abs/2206.11357 (2022) - [i22]Jin Gao, Jialing Zhang, Xihui Liu, Trevor Darrell, Evan Shelhamer, Dequan Wang:
Back to the Source: Diffusion-Driven Test-Time Adaptation. CoRR abs/2207.03442 (2022) - [i21]Fangyu Wu, Dequan Wang, Minjune Hwang, Chenhui Hao, Jiawei Lu, Jiamu Zhang, Christopher Chou, Trevor Darrell, Alexandre M. Bayen:
Decentralized Vehicle Coordination: The Berkeley DeepDrive Drone Dataset. CoRR abs/2209.08763 (2022) - [i20]Dequan Wang, Yifan Duan, Xiaoran Fan, Chengzhen Meng, Jianmin Ji, Yanyong Zhang:
MAROAM: Map-based Radar SLAM through Two-step Feature Selection. CoRR abs/2210.13797 (2022) - 2021
- [c15]Qijing Huang, Dequan Wang, Zhen Dong, Yizhao Gao, Yaohui Cai, Tian Li, Bichen Wu, Kurt Keutzer, John Wawrzynek:
CoDeNet: Efficient Deployment of Input-Adaptive Object Detection on Embedded FPGAs. FPGA 2021: 206-216 - [c14]Dequan Wang, Evan Shelhamer, Shaoteng Liu, Bruno A. Olshausen, Trevor Darrell:
Tent: Fully Test-Time Adaptation by Entropy Minimization. ICLR 2021 - [c13]Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael W. Mahoney, Joseph Gonzalez:
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training. ICML 2021: 1803-1813 - [i19]Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael W. Mahoney, Joseph E. Gonzalez:
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training. CoRR abs/2104.14129 (2021) - [i18]Dequan Wang, An Ju, Evan Shelhamer, David A. Wagner, Trevor Darrell:
Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks. CoRR abs/2105.08714 (2021) - [i17]Dequan Wang, Shaoteng Liu, Sayna Ebrahimi, Evan Shelhamer, Trevor Darrell:
On-target Adaptation. CoRR abs/2109.01087 (2021) - 2020
- [j2]Bahiyah Omar, Dequan Wang:
Watch, Share or Create: The Influence of Personality Traits and User Motivation on TikTok Mobile Video Usage. Int. J. Interact. Mob. Technol. 14(4): 121-137 (2020) - [i16]Qijing Huang, Dequan Wang, Yizhao Gao, Yaohui Cai, Zhen Dong, Bichen Wu, Kurt Keutzer, John Wawrzynek:
Algorithm-hardware Co-design for Deformable Convolution. CoRR abs/2002.08357 (2020) - [i15]Zhen Dong, Dequan Wang, Qijing Huang, Yizhao Gao, Yaohui Cai, Bichen Wu, Kurt Keutzer, John Wawrzynek:
CoDeNet: Algorithm-hardware Co-design for Deformable Convolution. CoRR abs/2006.08357 (2020) - [i14]Dequan Wang, Evan Shelhamer, Shaoteng Liu, Bruno A. Olshausen, Trevor Darrell:
Fully Test-time Adaptation by Entropy Minimization. CoRR abs/2006.10726 (2020) - [i13]Mong H. Ng, Kaahan Radia, Jianfei Chen, Dequan Wang, Ionel Gog, Joseph E. Gonzalez:
BEV-Seg: Bird's Eye View Semantic Segmentation Using Geometry and Semantic Point Cloud. CoRR abs/2006.11436 (2020)
2010 – 2019
- 2019
- [c12]Hou-Ning Hu, Qi-Zhi Cai, Dequan Wang, Ji Lin, Min Sun, Philipp Krähenbühl, Trevor Darrell, Fisher Yu:
Joint Monocular 3D Vehicle Detection and Tracking. ICCV 2019: 5389-5398 - [c11]Chiyu Max Jiang, Dequan Wang, Jingwei Huang, Philip Marcus, Matthias Nießner:
Convolutional Neural Networks on Non-uniform Geometrical Signals Using Euclidean Spectral Transformation. ICLR (Poster) 2019 - [c10]Dequan Wang, Coline Devin, Qi-Zhi Cai, Fisher Yu, Trevor Darrell:
Deep Object-Centric Policies for Autonomous Driving. ICRA 2019: 8853-8859 - [c9]Dequan Wang, Coline Devin, Qi-Zhi Cai, Philipp Krähenbühl, Trevor Darrell:
Monocular Plan View Networks for Autonomous Driving. IROS 2019: 2876-2883 - [c8]Qijing Huang, Dequan Wang, Yizhao Gao, Yaohui Cai, Zhen Dong, Bichen Wu, Kurt Keutzer, John Wawrzynek:
Algorithm-hardware Co-design for Deformable Convolution. EMC2@NeurIPS 2019: 48-51 - [i12]Chiyu Max Jiang, Dequan Wang, Jingwei Huang, Philip Marcus, Matthias Nießner:
Convolutional Neural Networks on non-uniform geometrical signals using Euclidean spectral transformation. CoRR abs/1901.02070 (2019) - [i11]Xingyi Zhou, Dequan Wang, Philipp Krähenbühl:
Objects as Points. CoRR abs/1904.07850 (2019) - [i10]Evan Shelhamer, Dequan Wang, Trevor Darrell:
Blurring the Line Between Structure and Learning to Optimize and Adapt Receptive Fields. CoRR abs/1904.11487 (2019) - [i9]Dequan Wang, Coline Devin, Qi-Zhi Cai, Philipp Krähenbühl, Trevor Darrell:
Monocular Plan View Networks for Autonomous Driving. CoRR abs/1905.06937 (2019) - [i8]Dequan Wang, Evan Shelhamer, Bruno A. Olshausen, Trevor Darrell:
Dynamic Scale Inference by Entropy Minimization. CoRR abs/1908.03182 (2019) - 2018
- [c7]Xingchao Peng, Ben Usman, Neela Kaushik, Dequan Wang, Judy Hoffman, Kate Saenko:
VisDA: A Synthetic-to-Real Benchmark for Visual Domain Adaptation. CVPR Workshops 2018: 2021-2026 - [c6]Fisher Yu, Dequan Wang, Evan Shelhamer, Trevor Darrell:
Deep Layer Aggregation. CVPR 2018: 2403-2412 - [c5]Fisher Yu, Dequan Wang, Evan Shelhamer, Trevor Darrell:
Learning Rich Image Representation with Deep Layer Aggregation. ICLR (Workshop) 2018 - [i7]Dequan Wang, Coline Devin, Qi-Zhi Cai, Fisher Yu, Trevor Darrell:
Deep Object Centric Policies for Autonomous Driving. CoRR abs/1811.05432 (2018) - [i6]Hou-Ning Hu, Qi-Zhi Cai, Dequan Wang, Ji Lin, Min Sun, Philipp Krähenbühl, Trevor Darrell, Fisher Yu:
Joint Monocular 3D Vehicle Detection and Tracking. CoRR abs/1811.10742 (2018) - 2017
- [c4]Zhiqiang Shen, Yu-Gang Jiang, Dequan Wang, Xiangyang Xue:
Iterative object and part transfer for fine-grained recognition. ICME 2017: 1470-1475 - [i5]Zhiqiang Shen, Yu-Gang Jiang, Dequan Wang, Xiangyang Xue:
Iterative Object and Part Transfer for Fine-Grained Recognition. CoRR abs/1703.09983 (2017) - [i4]Fisher Yu, Dequan Wang, Trevor Darrell:
Deep Layer Aggregation. CoRR abs/1707.06484 (2017) - [i3]Xingchao Peng, Ben Usman, Neela Kaushik, Judy Hoffman, Dequan Wang, Kate Saenko:
VisDA: The Visual Domain Adaptation Challenge. CoRR abs/1710.06924 (2017) - 2016
- [j1]Qiaojun Wang, Kai Zhang, Zhengzhang Chen, Dequan Wang, Guofei Jiang, Ivan Marsic:
Enhancing semi-supervised learning through label-aware base kernels. Neurocomputing 171: 1335-1343 (2016) - [i2]Judy Hoffman, Dequan Wang, Fisher Yu, Trevor Darrell:
FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation. CoRR abs/1612.02649 (2016) - 2015
- [c3]Yongxin Zhang, Qingzhong Li, Dequan Wang, Yanhui Ding, Congli Liu, Zhongmin Yan:
Matching Reviews to Object Based on 2-Stage CRF. APWeb 2015: 92-103 - [c2]Wei Zhang, Sheng Zeng, Dequan Wang, Xiangyang Xue:
Weakly supervised semantic segmentation for social images. CVPR 2015: 2718-2726 - [c1]Dequan Wang, Zhiqiang Shen, Jie Shao, Wei Zhang, Xiangyang Xue, Zheng Zhang:
Multiple Granularity Descriptors for Fine-Grained Categorization. ICCV 2015: 2399-2406 - [i1]Jie Shao, Dequan Wang, Xiangyang Xue, Zheng Zhang:
Learning to Point and Count. CoRR abs/1512.02326 (2015)
Coauthor Index
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last updated on 2024-11-27 21:22 CET by the dblp team
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