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Leveraging Bottom-Up and Top-Down Attention for Few-Shot Object
  Detection

Leveraging Bottom-Up and Top-Down Attention for Few-Shot Object Detection

23 July 2020
Xianyu Chen
Ming Jiang
Qi Zhao
    ObjD
ArXivPDFHTML

Papers citing "Leveraging Bottom-Up and Top-Down Attention for Few-Shot Object Detection"

5 / 5 papers shown
Title
A Comparative Review of Recent Few-Shot Object Detection Algorithms
A Comparative Review of Recent Few-Shot Object Detection Algorithms
Jiaxu Leng
Taiyue Chen
Gao Xinbo
Yongtao Yu
Ye Wang
Feng Gao
Wang Yue
ObjD
19
15
0
30 Oct 2021
Frustratingly Simple Few-Shot Object Detection
Frustratingly Simple Few-Shot Object Detection
Xin Wang
Thomas E. Huang
Trevor Darrell
Joseph E. Gonzalez
F. I. F. Richard Yu
ObjD
95
544
0
16 Mar 2020
Meta R-CNN : Towards General Solver for Instance-level Few-shot Learning
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
160
446
0
28 Sep 2019
Bayesian Model-Agnostic Meta-Learning
Bayesian Model-Agnostic Meta-Learning
Taesup Kim
Jaesik Yoon
Ousmane Amadou Dia
Sungwoong Kim
Yoshua Bengio
Sungjin Ahn
UQCV
BDL
202
498
0
11 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
329
11,684
0
09 Mar 2017
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