Exploring Effective Knowledge Transfer for Few-shot Object Detection

Exploring Effective Knowledge Transfer for Few-shot Object Detection

5 October 2022

Qingjie Liu

Yunhong Wang

Papers citing "Exploring Effective Knowledge Transfer for Few-shot Object Detection"

9 / 9 papers shown

Title
GRSDet: Learning to Generate Local Reverse Samples for Few-shot Object Detection Hefei Mei Taijin Zhao Shiyuan Tang Heqian Qiu Lanxiao Wang Minjian Zhang Fanman Meng Hongliang Li ObjD 11 1 0 27 Dec 2023
Hallucination Improves Few-Shot Object Detection Weilin Zhang Yu-xiong Wang ObjD 52 109 0 04 May 2021
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration Zhiqiang Shen Zechun Liu Jie Qin Lei Huang Kwang-Ting Cheng Marios Savvides UQCV SSL MQ 244 22 0 17 Feb 2021
Free Lunch for Few-shot Learning: Distribution Calibration Shuo Yang Lu Liu Min Xu OODD 199 316 0 16 Jan 2021
Frustratingly Simple Few-Shot Object Detection Xin Wang Thomas E. Huang Trevor Darrell Joseph E. Gonzalez F. I. F. Richard Yu ObjD 75 535 0 16 Mar 2020
Meta R-CNN : Towards General Solver for Instance-level Few-shot Learning Xiaopeng Yan Ziliang Chen Anni Xu Xiaoxi Wang Xiaodan Liang Liang Lin ObjD 151 440 0 28 Sep 2019
Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models Cheolhyoung Lee Kyunghyun Cho Wanmo Kang MoE 225 204 0 25 Sep 2019
Delta-encoder: an effective sample synthesis method for few-shot object recognition Eli Schwartz Leonid Karlinsky J. Shtok Sivan Harary Mattias Marder Rogerio Feris Abhishek Kumar Raja Giryes A. Bronstein 173 350 0 12 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 240 11,568 0 09 Mar 2017