Regional semantic contrast and aggregation for weakly supervised semantic segmentation
Learning semantic segmentation from weakly-labeled (eg, image tags only) data is
challenging since it is hard to infer dense object regions from sparse semantic tags. Despite …
challenging since it is hard to infer dense object regions from sparse semantic tags. Despite …
Machine learning empowering personalized medicine: A comprehensive review of medical image analysis methods
Artificial intelligence (AI) advancements, especially deep learning, have significantly
improved medical image processing and analysis in various tasks such as disease …
improved medical image processing and analysis in various tasks such as disease …
Remote sensing object detection meets deep learning: A metareview of challenges and advances
Remote sensing object detection (RSOD), one of the most fundamental and challenging
tasks in the remote sensing field, has received long-standing attention. In recent years, deep …
tasks in the remote sensing field, has received long-standing attention. In recent years, deep …
Fewer is more: Efficient object detection in large aerial images
Current mainstream object detection methods for large aerial images usually divide large
images into patches and then exhaustively detect the objects of interest on all patches, no …
images into patches and then exhaustively detect the objects of interest on all patches, no …
Mining high-quality pseudoinstance soft labels for weakly supervised object detection in remote sensing images
Weakly supervised object detection in remote sensing images (RSI) is still a challenge
because of the lack of instance-level labels, and many existing methods have two problems …
because of the lack of instance-level labels, and many existing methods have two problems …
[HTML][HTML] Semantic segmentation guided pseudo label mining and instance re-detection for weakly supervised object detection in remote sensing images
Weakly supervised object detection (WSOD) in remote sensing images (RSIs) has good
practical value because it only requires the image-level annotations. The existing methods …
practical value because it only requires the image-level annotations. The existing methods …
Weakly supervised rotation-invariant aerial object detection network
Object rotation is among long-standing, yet still unexplored, hard issues encountered in the
task of weakly supervised object detection (WSOD) from aerial images. Existing …
task of weakly supervised object detection (WSOD) from aerial images. Existing …
Weakly-supervised audio-visual segmentation
S Mo, B Raj - Advances in Neural Information Processing …, 2023 - proceedings.neurips.cc
Audio-visual segmentation is a challenging task that aims to predict pixel-level masks for
sound sources in a video. Previous work applied a comprehensive manually designed …
sound sources in a video. Previous work applied a comprehensive manually designed …
Gatector: A unified framework for gaze object prediction
Gaze object prediction is a newly proposed task that aims to discover the objects being
stared at by humans. It is of great application significance but still lacks a unified solution …
stared at by humans. It is of great application significance but still lacks a unified solution …
Hybrid attention-based U-shaped network for remote sensing image super-resolution
Recently, remote sensing image super-resolution (RSISR) has drawn considerable attention
and made great breakthroughs based on convolutional neural networks (CNNs). Due to the …
and made great breakthroughs based on convolutional neural networks (CNNs). Due to the …