What, How, and When Should Object Detectors Update in Continually
Changing Test Domains?

What, How, and When Should Object Detectors Update in Continually Changing Test Domains?

12 December 2023

Nojun Kwak

Papers citing "What, How, and When Should Object Detectors Update in Continually Changing Test Domains?"

9 / 9 papers shown

Title
PointSAM: Pointly-Supervised Segment Anything Model for Remote Sensing Images Nanqing Liu Xun Xu Yongyi Su Haojie Zhang Heng-Chao Li VLM 30 14 0 20 Sep 2024
Hyperparameters in Continual Learning: A Reality Check Sungmin Cha Kyunghyun Cho CLL 68 2 0 14 Mar 2024
Energy-Based Test Sample Adaptation for Domain Generalization Zehao Xiao Xiantong Zhen Shengcai Liao Cees G. M. Snoek TTA 38 17 0 22 Feb 2023
DELTA: degradation-free fully test-time adaptation Bowen Zhao Chen Chen Shutao Xia TTA 46 55 0 30 Jan 2023
TeST: Test-time Self-Training under Distribution Shift Samarth Sinha Peter V. Gehler Francesco Locatello Bernt Schiele TTA OOD 24 22 0 23 Sep 2022
AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition Shoufa Chen Chongjian Ge Zhan Tong Jiangliu Wang Yibing Song Jue Wang Ping Luo 141 631 0 26 May 2022
TTAPS: Test-Time Adaption by Aligning Prototypes using Self-Supervision Alexander Bartler Florian Bender Felix Wiewel B. Yang TTA 33 9 0 18 May 2022
Unbiased Mean Teacher for Cross-domain Object Detection Jinhong Deng Wen Li Yuhua Chen Lixin Duan 73 280 0 02 Mar 2020
Feature Pyramid Networks for Object Detection Tsung-Yi Lin Piotr Dollár Ross B. Girshick Kaiming He Bharath Hariharan Serge J. Belongie ObjD 166 21,643 0 09 Dec 2016