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Xiaoqi Li
Xiaoqi Li
Peking University
Verified email at columbia.edu
Title
Cited by
Cited by
Year
Towards accurate high resolution satellite image semantic segmentation
M Wu, C Zhang, J Liu, L Zhou, X Li
Ieee Access 7, 55609-55619, 2019
972019
Renderocc: Vision-centric 3d occupancy prediction with 2d rendering supervision
M Pan, J Liu, R Zhang, P Huang, X Li, L Liu, S Zhang
International Conference on Robotics and Automation (ICRA), 2023
352023
Lidar-llm: Exploring the potential of large language models for 3d lidar understanding
S Yang, J Liu, R Zhang, M Pan, Z Guo, X Li, Z Chen, P Gao, Y Guo, ...
arXiv preprint arXiv:2312.14074, 2023
312023
Overfitting the data: Compact neural video delivery via content-aware feature modulation
J Liu, M Lu, K Chen, X Li, S Wang, Z Wang, E Wu, Y Chen, C Zhang, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
282021
Exploring sparse visual prompt for cross-domain semantic segmentation
S Yang, J Wu, J Liu, X Li, Q Zhang, M Pan, S Zhang
arXiv preprint arXiv:2303.09792 1, 2023
222023
Adaptive patch exiting for scalable single image super-resolution
S Wang, J Liu, K Chen, X Li, M Lu, Y Guo
European Conference on Computer Vision, 292-307, 2022
222022
Discuss before moving: Visual language navigation via multi-expert discussions
Y Long, X Li, W Cai, H Dong
International Conference on Robotics and Automation (ICRA), 2023
212023
Manipllm: Embodied multimodal large language model for object-centric robotic manipulation
X Li, M Zhang, Y Geng, H Geng, Y Long, Y Shen, R Zhang, J Liu, H Dong
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024
162024
Efficient meta-tuning for content-aware neural video delivery
X Li, J Liu, S Wang, C Lyu, M Lu, Y Chen, A Yao, Y Guo, S Zhang
European Conference on Computer Vision, 308-324, 2022
102022
Manipvqa: Injecting robotic affordance and physically grounded information into multi-modal large language models
S Huang, I Ponomarenko, Z Jiang, X Li, X Hu, P Gao, H Li, H Dong
International Conference on Intelligent Robots and Systems (IROS), 2024
92024
RoboMamba: Multimodal State Space Model for Efficient Robot Reasoning and Manipulation
J Liu, M Liu, Z Wang, L Lee, K Zhou, P An, S Yang, R Zhang, Y Guo, ...
arXiv preprint arXiv:2406.04339, 2024
82024
Exploring sparse visual prompt for domain adaptive dense prediction
S Yang, J Wu, J Liu, X Li, Q Zhang, M Pan, Y Gan, Z Chen, S Zhang
Proceedings of the AAAI Conference on Artificial Intelligence 38 (15), 16334 …, 2024
82024
Find what you want: learning demand-conditioned object attribute space for demand-driven navigation
H Wang, AGH Chen, X Li, M Wu, H Dong
Advances in Neural Information Processing Systems 36, 2024
82024
Heart rate estimation from facial videos based on convolutional neural network
W Yang, X Li, B Zhang
2018 International Conference on Network Infrastructure and Digital Content …, 2018
82018
Distribution-aware continual test time adaptation for semantic segmentation
J Ni, S Yang, J Liu, X Li, W Jiao, R Xu, Z Chen, Y Liu, S Zhang
International Conference on Robotics and Automation (ICRA), 2023
72023
Rgbmanip: Monocular image-based robotic manipulation through active object pose estimation
B An, Y Geng, K Chen, X Li, Q Dou, H Dong
International Conference on Robotics and Automation (ICRA), 2023
62023
Samplingaug: On the importance of patch sampling augmentation for single image super-resolution
S Wang, M Lu, K Chen, J Liu, X Li, M Wu
arXiv preprint arXiv:2111.15185, 2021
62021
Naturalvlm: Leveraging fine-grained natural language for affordance-guided visual manipulation
R Xu, Y Shen, X Li, R Wu, H Dong
arXiv preprint arXiv:2403.08355, 2024
52024
Multi-latent Space Alignments for Unsupervised Domain Adaptation in Multi-view 3D Object Detection
J Liu, R Zhang, X Chi, X Li, M Lu, Y Guo, S Zhang
International Conference on Robotics and Automation (ICRA), 2022
52022
Self-Corrected Multimodal Large Language Model for End-to-End Robot Manipulation
J Liu, C Li, G Wang, L Lee, K Zhou, S Chen, C Xiong, J Ge, R Zhang, ...
arXiv preprint arXiv:2405.17418, 2024
42024
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