Advances in deep concealed scene understanding
Concealed scene understanding (CSU) is a hot computer vision topic aiming to perceive
objects exhibiting camouflage. The current boom in terms of techniques and applications …
objects exhibiting camouflage. The current boom in terms of techniques and applications …
A systematic review of image-level camouflaged object detection with deep learning
Y Liang, G Qin, M Sun, X Wang, J Yan, Z Zhang - Neurocomputing, 2024 - Elsevier
Camouflaged object detection (COD) aims to search and identify disguised objects that are
hidden in their surrounding environment, thereby deceiving the human visual system. As an …
hidden in their surrounding environment, thereby deceiving the human visual system. As an …
Alignment before aggregation: trajectory memory retrieval network for video object segmentation
Memory-based methods in semi-supervised video object segmentation task achieve
competitive performance by performing dense matching between query and memory frames …
competitive performance by performing dense matching between query and memory frames …
Focus on query: Adversarial mining transformer for few-shot segmentation
Few-shot segmentation (FSS) aims to segment objects of new categories given only a
handful of annotated samples. Previous works focus their efforts on exploring the support …
handful of annotated samples. Previous works focus their efforts on exploring the support …
Adaptive template transformer for mitochondria segmentation in electron microscopy images
Mitochondria, as tiny structures within the cell, are of significant importance to study cell
functions for biological and clinical analysis. And exploring how to automatically segment …
functions for biological and clinical analysis. And exploring how to automatically segment …
Pay attention to target: Relation-aware temporal consistency for domain adaptive video semantic segmentation
Video semantic segmentation has achieved conspicuous achievements attributed to the
development of deep learning, but suffers from labor-intensive annotated training data …
development of deep learning, but suffers from labor-intensive annotated training data …
[PDF][PDF] Appearance Prompt Vision Transformer for Connectome Reconstruction.
Neural connectivity reconstruction aims to understand the function of biological
reconstruction and promote basic scientific research. The intricate morphology and densely …
reconstruction and promote basic scientific research. The intricate morphology and densely …
Structure-decoupled adaptive part alignment network for domain adaptive mitochondria segmentation
Existing methods for unsupervised domain adaptive mitochondria segmentation perform
feature alignment via adversarial learning, and achieve promising performance. However …
feature alignment via adversarial learning, and achieve promising performance. However …
Electron microscopy images as set of fragments for mitochondrial segmentation
Automatic mitochondrial segmentation enjoys great popularity with the development of deep
learning. However, the coarse prediction raised by the presence of regular 3D grids in …
learning. However, the coarse prediction raised by the presence of regular 3D grids in …
[PDF][PDF] Aggregation and purification: dual enhancement network for point cloud few-shot segmentation
Point cloud few-shot semantic segmentation (PCFSS) aims to segment objects within query
samples of new categories given only a handful of annotated support samples. Although PC …
samples of new categories given only a handful of annotated support samples. Although PC …