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AdaTreeFormer: Few Shot Domain Adaptation for Tree Counting from a
  Single High-Resolution Image

AdaTreeFormer: Few Shot Domain Adaptation for Tree Counting from a Single High-Resolution Image

5 February 2024
H. A. Amirkolaee
Miaojing Shi
Lianghua He
Mark Mulligan
ArXivPDFHTML

Papers citing "AdaTreeFormer: Few Shot Domain Adaptation for Tree Counting from a Single High-Resolution Image"

5 / 5 papers shown
Title
Generating Pseudo-labels Adaptively for Few-shot Model-Agnostic
  Meta-Learning
Generating Pseudo-labels Adaptively for Few-shot Model-Agnostic Meta-Learning
Guodong Liu
Tongling Wang
Shuoxi Zhang
Kun He
33
1
0
09 Jul 2022
Few-Shot Adaptation of Pre-Trained Networks for Domain Shift
Few-Shot Adaptation of Pre-Trained Networks for Domain Shift
Wenyu Zhang
Li Shen
Wanyue Zhang
Chuan-Sheng Foo
TTA
52
17
0
30 May 2022
AdaCrowd: Unlabeled Scene Adaptation for Crowd Counting
AdaCrowd: Unlabeled Scene Adaptation for Crowd Counting
Mahesh Kumar Krishna Reddy
Mrigank Rochan
Yiwei Lu
Yang Wang
30
25
0
23 Oct 2020
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
338
11,684
0
09 Mar 2017
You Only Look Once: Unified, Real-Time Object Detection
You Only Look Once: Unified, Real-Time Object Detection
Joseph Redmon
S. Divvala
Ross B. Girshick
Ali Farhadi
ObjD
292
36,335
0
08 Jun 2015
1