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Jiteng Mu
Jiteng Mu
Verified email at ucsd.edu - Homepage
Title
Cited by
Cited by
Year
Learning from synthetic animals
J Mu, W Qiu, GD Hager, AL Yuille
Computer Vision and Pattern Recognition (CVPR), 12386-12395, 2020
1142020
A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation
J Mu, W Qiu, A Kortylewski, A Yuille, N Vasconcelos, X Wang
International Conference on Computer Vision (ICCV), 2021
792021
Learning Part Segmentation through Unsupervised Domain Adaptation from Synthetic Vehicles
Q Liu, A Kortylewski, Z Zhang, Z Li, M Guo, Q Liu, X Yuan, J Mu, W Qiu, ...
Computer Vision and Pattern Recognition (CVPR), 2022
31*2022
CoordGAN: Self-Supervised Dense Correspondences Emerge from GANs
J Mu, S De Mello, Z Yu, N Vasconcelos, X Wang, J Kautz, S Liu
Computer Vision and Pattern Recognition (CVPR), 2022
142022
A new efficient real-time arbitrary colored ball recognition method for a humanoid soccer robot
J Mu, Y Li
2016 12th World Congress on Intelligent Control and Automation (WCICA), 494-499, 2016
102016
Multi-mosquito object detection and 2D pose estimation for automation of PfSPZ malaria vaccine production
H Wu, J Mu, T Da, M Xu, RH Taylor, I Iordachita, GS Chirikjian
2019 IEEE 15th International Conference on Automation Science and …, 2019
92019
ActorsNeRF: Animatable Few-shot Human Rendering with Generalizable NeRFs
J Mu, S Sang, N Vasconcelos, X Wang
International Conference on Computer Vision (ICCV), 2023
82023
Learning Part Segmentation from Synthetic Animals
J Peng, J He, P Kaushik, Z Xiao, J Mu, A Yuille
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024
2024
Learning dense correspondences for images
S Liu, J Mu, S De Mello, Z Yu, J Kautz
US Patent App. 17/929,182, 2023
2023
CoordGAN: Self-Supervised Dense Correspondences Emerge from GANs Supplementary Materials
J Mu, S De Mello, Z Yu, N Vasconcelos, X Wang, J Kautz, S Liu
CCVL
J Mu, W Qiu, GD Hager, A Yuille
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