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Detect, Augment, Compose, and Adapt: Four Steps for Unsupervised Domain Adaptation in Object Detection
29 August 2023
M. L. Mekhalfi
Davide Boscaini
Fabio Poiesi
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Papers citing
"Detect, Augment, Compose, and Adapt: Four Steps for Unsupervised Domain Adaptation in Object Detection"
7 / 7 papers shown
Title
Leveraging Sparse Annotations for Leukemia Diagnosis on the Large Leukemia Dataset
Abdul Rehman
Talha Meraj
A. Minhas
A. Imran
Mohsen Ali
Waqas Sultani
M. Shah
47
0
0
03 Apr 2025
A Large-scale Multi Domain Leukemia Dataset for the White Blood Cells Detection with Morphological Attributes for Explainability
Abdul Rehman
Talha Meraj
A. Minhas
Ayisha Imran
Mohsen Ali
Waqas Sultani
16
2
0
17 May 2024
Wild Berry image dataset collected in Finnish forests and peatlands using drones
Luigi Riz
Sergio Povoli
Andrea Caraffa
Davide Boscaini
M. L. Mekhalfi
...
Elisa Castelli
Giacomo Piccinini
L. Marchesotti
Micael S. Couceiro
Fabio Poiesi
21
0
0
13 May 2024
Cross-Domain Adaptive Teacher for Object Detection
Yu-Jhe Li
Xiaoliang Dai
Chih-Yao Ma
Yen-Cheng Liu
Kan Chen
Bichen Wu
Zijian He
Kris M. Kitani
Peter Vajda
ObjD
44
170
0
25 Nov 2021
Seeking Similarities over Differences: Similarity-based Domain Alignment for Adaptive Object Detection
Farzaneh Rezaeianaran
Rakshith Shetty
Rahaf Aljundi
Daniel Olmeda Reino
Shanshan Zhang
Bernt Schiele
OOD
37
76
0
04 Oct 2021
DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation
Xinyi Wu
Zhenyao Wu
Haojie Guo
L. Ju
Song Wang
82
143
0
22 Apr 2021
Adapting Object Detectors with Conditional Domain Normalization
Peng Su
Kun Wang
Xingyu Zeng
Shixiang Tang
Dapeng Chen
Di Qiu
Xiaogang Wang
47
84
0
16 Mar 2020
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