Weakly supervised object localization and detection: A survey
As an emerging and challenging problem in the computer vision community, weakly
supervised object localization and detection plays an important role for developing new …
supervised object localization and detection plays an important role for developing new …
Detecting twenty-thousand classes using image-level supervision
Current object detectors are limited in vocabulary size due to the small scale of detection
datasets. Image classifiers, on the other hand, reason about much larger vocabularies, as …
datasets. Image classifiers, on the other hand, reason about much larger vocabularies, as …
Bridging the gap between object and image-level representations for open-vocabulary detection
H Bangalath, M Maaz, MU Khattak… - Advances in …, 2022 - proceedings.neurips.cc
Existing open-vocabulary object detectors typically enlarge their vocabulary sizes by
leveraging different forms of weak supervision. This helps generalize to novel objects at …
leveraging different forms of weak supervision. This helps generalize to novel objects at …
[HTML][HTML] HCPNet: Learning discriminative prototypes for few-shot remote sensing image scene classification
J Zhu, K Yang, N Guan, X Yi, C Qiu - International Journal of Applied Earth …, 2023 - Elsevier
Few-shot learning is an important and challenging research topic for remote sensing image
scene classification. Many existing approaches address this challenge by using meta …
scene classification. Many existing approaches address this challenge by using meta …
Instance-aware, context-focused, and memory-efficient weakly supervised object detection
Weakly supervised learning has emerged as a compelling tool for object detection by
reducing the need for strong supervision during training. However, major challenges …
reducing the need for strong supervision during training. However, major challenges …
Proposal-based multiple instance learning for weakly-supervised temporal action localization
Weakly-supervised temporal action localization aims to localize and recognize actions in
untrimmed videos with only video-level category labels during training. Without instance …
untrimmed videos with only video-level category labels during training. Without instance …
Weakly supervised object detection using proposal-and semantic-level relationships
In recent years, weakly supervised object detection has attracted great attention in the
computer vision community. Although numerous deep learning-based approaches have …
computer vision community. Although numerous deep learning-based approaches have …
Selecting high-quality proposals for weakly supervised object detection with bottom-up aggregated attention and phase-aware loss
Weakly supervised object detection (WSOD) has received widespread attention since it
requires only image-category annotations for detector training. Many advanced approaches …
requires only image-category annotations for detector training. Many advanced approaches …
High-quality proposals for weakly supervised object detection
G Cheng, J Yang, D Gao, L Guo… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Despite significant efforts made so far for Weakly Supervised Object Detection (WSOD),
proposal generation and proposal selection are still two major challenges. In this paper, we …
proposal generation and proposal selection are still two major challenges. In this paper, we …
Erasing integrated learning: A simple yet effective approach for weakly supervised object localization
Weakly supervised object localization (WSOL) aims to localize object with only weak
supervision like image-level labels. However, a long-standing problem for available …
supervision like image-level labels. However, a long-standing problem for available …