Lu Jiang
Lu Jiang
Research Scientist, TikTok & Adjunct Faculty, CMU
Verified email at - Homepage
Cited by
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Mentornet: Learning data-driven curriculum for very deep neural networks on corrupted labels
L Jiang, Z Zhou, T Leung, LJ Li, L Fei-Fei
ICML, 2018
Contrastive Adaptation Network for Unsupervised Domain Adaptation
G Kang, L Jiang, Y Yang, AG Hauptmann
CVPR, 2019
Confident learning: Estimating uncertainty in dataset labels
C Northcutt, L Jiang, I Chuang
Journal of Artificial Intelligence Research 70, 1373-1411, 2021
Self-paced curriculum learning
L Jiang, D Meng, Q Zhao, S Shan, A Hauptmann
AAAI, 2015
Peeking into the Future: Predicting Future Person Activities and Locations in Videos
J Liang, L Jiang, JC Niebles, A Hauptmann, L Fei-Fei
CVPR, 2019
Self-paced learning with diversity
L Jiang, D Meng, SI Yu, Z Lan, S Shan, A Hauptmann
NeurIPS, 2014
Eidetic 3D LSTM: A Model for Video Prediction and Beyond
Y Wang, L Jiang, MH Yang, LJ Li, M Long, L Fei-Fei
ICLR, 2019
Maskgit: Masked generative image transformer
H Chang, H Zhang, L Jiang, C Liu, WT Freeman
CVPR, 2022
Composing Text and Image for Image Retrieval-An Empirical Odyssey
N Vo, L Jiang, C Sun, K Murphy, LJ Li, L Fei-Fei, J Hays
CVPR, 2019
Easy samples first: Self-paced reranking for zero-example multimedia search
L Jiang, D Meng, T Mitamura, AG Hauptmann
ACM international conference on Multimedia, 2014
Muse: Text-to-image generation via masked generative transformers
H Chang, H Zhang, J Barber, AJ Maschinot, J Lezama, L Jiang, MH Yang, ...
ICML, 2023
Robust Neural Machine Translation with Doubly Adversarial Inputs
Y Cheng, L Jiang, W Macherey
ACL, 2019
Beyond Synthetic Noise: Deep Learning on Controlled Noisy Labels
L Jiang, D Huang, L Mason, W Yang
ICML, 2020
Vitgan: Training gans with vision transformers
K Lee, H Chang, L Jiang, H Zhang, Z Tu, C Liu
ICLR, 2022
Self-paced learning for matrix factorization
Q Zhao, D Meng, L Jiang, Q Xie, Z Xu, A Hauptmann
AAAI, 2015
The garden of forking paths: Towards multi-future trajectory prediction
J Liang, L Jiang, K Murphy, T Yu, A Hauptmann
CVPR, 2020
A self-paced multiple-instance learning framework for co-saliency detection
D Zhang, D Meng, C Li, L Jiang, Q Zhao, J Han
ICCV, 594-602, 2015
Regularizing Generative Adversarial Networks under Limited Data
HY Tseng, L Jiang, C Liu, MH Yang, W Yang
CVPR, 2021
Revealing event saliency in unconstrained video collection
D Zhang, J Han, L Jiang, S Ye, X Chang
IEEE Transactions on Image Processing 26 (4), 1746-1758, 2017
A theoretical understanding of self-paced learning
D Meng, Q Zhao, L Jiang
Information Sciences 414, 319-328, 2017
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