CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features Paper • 1905.04899 • Published May 13, 2019
SeiT: Storage-Efficient Vision Training with Tokens Using 1% of Pixel Storage Paper • 2303.11114 • Published Mar 20, 2023
CompoDiff: Versatile Composed Image Retrieval With Latent Diffusion Paper • 2303.11916 • Published Mar 21, 2023
ViDT: An Efficient and Effective Fully Transformer-based Object Detector Paper • 2110.03921 • Published Oct 8, 2021 • 1
ECCV Caption: Correcting False Negatives by Collecting Machine-and-Human-verified Image-Caption Associations for MS-COCO Paper • 2204.03359 • Published Apr 7, 2022
AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights Paper • 2006.08217 • Published Jun 15, 2020
Language-only Efficient Training of Zero-shot Composed Image Retrieval Paper • 2312.01998 • Published Dec 4, 2023
Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels Paper • 2101.05022 • Published Jan 13, 2021
Evaluating Weakly Supervised Object Localization Methods Right Paper • 2001.07437 • Published Jan 21, 2020
Learning De-biased Representations with Biased Representations Paper • 1910.02806 • Published Oct 7, 2019
An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods Paper • 2003.03879 • Published Mar 9, 2020
Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective Paper • 2110.03095 • Published Oct 6, 2021
Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and Datasets Paper • 2007.04178 • Published Jul 8, 2020
Neural Hybrid Automata: Learning Dynamics with Multiple Modes and Stochastic Transitions Paper • 2106.04165 • Published Jun 8, 2021
An Extendable, Efficient and Effective Transformer-based Object Detector Paper • 2204.07962 • Published Apr 17, 2022