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2020 – today
- 2026
[j1]Shunlin Lu, Hailing Zhou, David T. Nguyen, Mats Isaksson, Tao Peng, Chee Peng Lim, Saeid Nahavandi, Lei Wei:
Neural-symbolic framework for dynamic hazard detection through compositional visual reasoning. J. Ambient Intell. Humaniz. Comput. 17(3): 979-994 (2026)- 2025
- [c9]Shunlin Lu, Jingbo Wang, Zeyu Lu, Ling-Hao Chen, Wenxun Dai, Junting Dong, Zhiyang Dou, Bo Dai, Ruimao Zhang:
ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model. CVPR 2025: 27872-27882 - [c8]Mingze Sun, Shiwei Mao, Keyi Chen, Yurun Chen, Shunlin Lu, Jingbo Wang, Junting Dong, Ruqi Huang:
ARMO: Autoregressive Rigging for Multi-Category Objects. ICCV 2025: 7721-7730 - [c7]Lixing Xiao, Shunlin Lu, Huaijin Pi, Ke Fan, Liang Pan, Yueer Zhou, Ziyong Feng, Xiaowei Zhou, Sida Peng, Jingbo Wang:
MotionStreamer: Streaming Motion Generation via Diffusion-Based Autoregressive Model in Causal Latent Space. ICCV 2025: 10086-10096 - [c6]Ke Fan, Shunlin Lu, Minyue Dai, Runyi Yu, Lixing Xiao, Zhiyang Dou, Junting Dong, Lizhuang Ma, Jingbo Wang:
Go to Zero: Towards Zero-Shot Motion Generation with Million-Scale Data. ICCV 2025: 13336-13348 - [i14]Yuhong Zhang, Jing Lin, Ailing Zeng, Guanlin Wu
, Shunlin Lu, Yurong Fu, Yuanhao Cai, Ruimao Zhang, Haoqian Wang, Lei Zhang:
Motion-X++: A Large-Scale Multimodal 3D Whole-body Human Motion Dataset. CoRR abs/2501.05098 (2025) - [i13]Lixing Xiao, Shunlin Lu, Huaijin Pi, Ke Fan, Liang Pan, Yueer Zhou, Ziyong Feng, Xiaowei Zhou, Sida Peng, Jingbo Wang:
MotionStreamer: Streaming Motion Generation via Diffusion-based Autoregressive Model in Causal Latent Space. CoRR abs/2503.15451 (2025) - [i12]Mingze Sun, Shiwei Mao, Keyi Chen, Yurun Chen, Shunlin Lu, Jingbo Wang, Junting Dong, Ruqi Huang:
ARMO: Autoregressive Rigging for Multi-Category Objects. CoRR abs/2503.20663 (2025) - [i11]Ke Fan, Shunlin Lu, Minyue Dai, Runyi Yu, Lixing Xiao, Zhiyang Dou, Junting Dong, Lizhuang Ma, Jingbo Wang:
Go to Zero: Towards Zero-shot Motion Generation with Million-scale Data. CoRR abs/2507.07095 (2025) - [i10]Weishuai Zeng, Shunlin Lu, Kangning Yin, Xiaojie Niu, Minyue Dai, Jingbo Wang, Jiangmiao Pang:
Behavior Foundation Model for Humanoid Robots. CoRR abs/2509.13780 (2025) - [i9]Yiming Hao, Mutian Xu, Chongjie Ye, Jie Qin, Shunlin Lu, Yipeng Qin, Xiaoguang Han:
LoFA: Learning to Predict Personalized Priors for Fast Adaptation of Visual Generative Models. CoRR abs/2512.08785 (2025) - 2024
- [c5]Shunlin Lu, Ling-Hao Chen, Ailing Zeng, Jing Lin, Ruimao Zhang, Lei Zhang, Heung-Yeung Shum:
HumanTOMATO: Text-aligned Whole-body Motion Generation. ICML 2024: 32939-32977 - [i8]Ling-Hao Chen, Shunlin Lu, Ailing Zeng, Hao Zhang, Benyou Wang, Ruimao Zhang, Lei Zhang:
MotionLLM: Understanding Human Behaviors from Human Motions and Videos. CoRR abs/2405.20340 (2024) - [i7]Yuzhou Huang, Yiran Qin, Shunlin Lu, Xintao Wang, Rui Huang, Ying Shan, Ruimao Zhang:
Story3D-Agent: Exploring 3D Storytelling Visualization with Large Language Models. CoRR abs/2408.11801 (2024) - [i6]Ling-Hao Chen, Wenxun Dai, Xuan Ju, Shunlin Lu, Lei Zhang:
MotionCLR: Motion Generation and Training-free Editing via Understanding Attention Mechanisms. CoRR abs/2410.18977 (2024) - [i5]Shunlin Lu, Jingbo Wang, Zeyu Lu, Ling-Hao Chen, Wenxun Dai, Junting Dong, Zhiyang Dou, Bo Dai, Ruimao Zhang:
ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model. CoRR abs/2412.14559 (2024) - 2023
- [c4]Souvik Kundu, Sairam Sundaresan, Sharath Nittur Sridhar, Shunlin Lu, Han Tang, Peter A. Beerel:
Sparse Mixture Once-for-all Adversarial Training for Efficient in-situ Trade-off between Accuracy and Robustness of DNNs. ICASSP 2023: 1-5 - [c3]Souvik Kundu, Shunlin Lu, Yuke Zhang, Jacqueline Tiffany Liu, Peter A. Beerel:
Learning to Linearize Deep Neural Networks for Secure and Efficient Private Inference. ICLR 2023 - [c2]Jing Lin, Ailing Zeng, Shunlin Lu, Yuanhao Cai, Ruimao Zhang, Haoqian Wang, Lei Zhang:
Motion-X: A Large-scale 3D Expressive Whole-body Human Motion Dataset. NeurIPS 2023 - [i4]Souvik Kundu, Shunlin Lu, Yuke Zhang, Jacqueline Tiffany Liu, Peter A. Beerel:
Learning to Linearize Deep Neural Networks for Secure and Efficient Private Inference. CoRR abs/2301.09254 (2023) - [i3]Souvik Kundu, Sairam Sundaresan, Sharath Nittur Sridhar, Shunlin Lu, Han Tang, Peter A. Beerel:
Sparse Mixture Once-for-all Adversarial Training for Efficient In-Situ Trade-Off Between Accuracy and Robustness of DNNs. CoRR abs/2302.03523 (2023) - [i2]Jing Lin, Ailing Zeng, Shunlin Lu, Yuanhao Cai, Ruimao Zhang, Haoqian Wang, Lei Zhang:
Motion-X: A Large-scale 3D Expressive Whole-body Human Motion Dataset. CoRR abs/2307.00818 (2023) - [i1]Shunlin Lu, Ling-Hao Chen, Ailing Zeng, Jing Lin, Ruimao Zhang, Lei Zhang, Heung-Yeung Shum:
HumanTOMATO: Text-aligned Whole-body Motion Generation. CoRR abs/2310.12978 (2023) - 2022
- [c1]Gourav Datta, Souvik Kundu, Zihan Yin, Joe Mathai, Zeyu Liu, Zixu Wang, Mulin Tian, Shunlin Lu, Ravi Teja Lakkireddy, Andrew G. Schmidt, Wael Abd-Almageed, Ajey P. Jacob, Akhilesh R. Jaiswal, Peter A. Beerel:
P2M-DeTrack: Processing-in-Pixel-in-Memory for Energy-efficient and Real-Time Multi-Object Detection and Tracking. VLSI-SoC 2022: 1-6
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last updated on 2026-06-27 06:53 CEST by the dblp team
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