"synthetic data training" Papers
12 papers found
Conference
Amodal3R: Amodal 3D Reconstruction from Occluded 2D Images
Tianhao Wu, Chuanxia Zheng, Frank Guan et al.
ICCV 2025arXiv:2503.13439
23
citations
CADCrafter: Generating Computer-Aided Design Models from Unconstrained Images
Chen Cheng, Jiacheng Wei, Tianrun Chen et al.
CVPR 2025arXiv:2504.04753
15
citations
Escaping Collapse: The Strength of Weak Data for Large Language Model Training
Kareem Amin, Sara Babakniya, Alex Bie et al.
NEURIPS 2025arXiv:2502.08924
11
citations
Multi-View 3D Point Tracking
Frano Rajič, Haofei Xu, Marko Mihajlovic et al.
ICCV 2025arXiv:2508.21060
4
citations
Self-Verification Provably Prevents Model Collapse in Recursive Synthetic Training
Shi Fu, Yingjie Wang, Yuzhu Chen et al.
NEURIPS 2025
DataDream: Few-shot Guided Dataset Generation
Jae Myung Kim, Jessica Bader, Stephan Alaniz et al.
ECCV 2024arXiv:2407.10910
23
citations
Dense Optical Tracking: Connecting the Dots
Guillaume Le Moing, Jean Ponce, Cordelia Schmid
CVPR 2024highlightarXiv:2312.00786
54
citations
Lost and Found: Overcoming Detector Failures in Online Multi-Object Tracking
Lorenzo Vaquero, Yihong XU, Xavier Alameda-Pineda et al.
ECCV 2024arXiv:2407.10151
Mind The Edge: Refining Depth Edges in Sparsely-Supervised Monocular Depth Estimation
Lior Talker, Aviad Cohen, Erez Yosef et al.
CVPR 2024arXiv:2212.05315
10
citations
Self-Correcting Self-Consuming Loops for Generative Model Training
Nate Gillman, Michael Freeman, Daksh Aggarwal et al.
ICML 2024arXiv:2402.07087
24
citations
Towards Theoretical Understandings of Self-Consuming Generative Models
Shi Fu, Sen Zhang, Yingjie Wang et al.
ICML 2024arXiv:2402.11778
22
citations
What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation
Aaditya Singh, Ted Moskovitz, Feilx Hill et al.
ICML 2024spotlightarXiv:2404.07129
64
citations