Improving Fine-tuning of Self-supervised Models with Contrastive Initialization

30 July 2022

Papers citing "Improving Fine-tuning of Self-supervised Models with Contrastive Initialization"

9 / 9 papers shown

Title
BiSSL: Enhancing the Alignment Between Self-Supervised Pretraining and Downstream Fine-Tuning via Bilevel Optimization Gustav Wagner Zakarias Lars Kai Hansen Zheng-Hua Tan 114 0 0 03 Oct 2024
Finetuning Pre-trained Model with Limited Data for LiDAR-based 3D Object Detection by Bridging Domain Gaps Jiyun Jang Mincheol Chang Jongwon Park Jinkyu Kim 3DPC 94 0 0 02 Oct 2024
How Far Can In-Context Alignment Go? Exploring the State of In-Context Alignment Heyan Huang Yinghao Li Huashan Sun Yu Bai Yang Gao 96 4 0 17 Jun 2024
Concept-wise Fine-tuning Matters in Preventing Negative Transfer Yunqiao Yang Long-Kai Huang Ying Wei 86 2 0 12 Nov 2023
Controlled Randomness Improves the Performance of Transformer Models Tobias Deuβer Cong Zhao Wolfgang Krämer David Leonhard Christian Bauckhage R. Sifa 68 1 0 20 Oct 2023
Robustifying Token Attention for Vision Transformers Yong Guo David Stutz Bernt Schiele ViT 131 27 0 20 Mar 2023
Boosting Semi-Supervised Learning with Contrastive Complementary Labeling Qinyi Deng Yong Guo Zhibang Yang Haolin Pan Jian Chen 121 11 0 13 Dec 2022
Downscaled Representation Matters: Improving Image Rescaling with Collaborative Downscaled Images Bing Xu Yong Guo Luo Jiang Mianjie Yu Jian Chen 103 15 0 19 Nov 2022
ClusterFit: Improving Generalization of Visual Representations Xueting Yan Ishan Misra Abhinav Gupta Deepti Ghadiyaram D. Mahajan SSL VLM 146 134 0 06 Dec 2019