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Visual semantic segmentation based on few/zero-shot learning: An overview
Visual semantic segmentation aims at separating a visual sample into diverse blocks with
specific semantic attributes and identifying the category for each block, and it plays a crucial …
specific semantic attributes and identifying the category for each block, and it plays a crucial …
Few-shot object detection on remote sensing images
In this article, we deal with the problem of object detection on remote sensing images.
Previous researchers have developed numerous deep convolutional neural network (CNN) …
Previous researchers have developed numerous deep convolutional neural network (CNN) …
Partslip: Low-shot part segmentation for 3d point clouds via pretrained image-language models
Generalizable 3D part segmentation is important but challenging in vision and robotics.
Training deep models via conventional supervised methods requires large-scale 3D …
Training deep models via conventional supervised methods requires large-scale 3D …
Few-shot point cloud semantic segmentation via contrastive self-supervision and multi-resolution attention
This paper presents an effective few-shot point cloud semantic segmentation approach for
real-world applications. Existing few-shot segmentation methods on point cloud heavily rely …
real-world applications. Existing few-shot segmentation methods on point cloud heavily rely …
: 3D Object Part Segmentation by 2D Semantic Correspondences
Abstract 3D object part segmentation is essential in computer vision applications. While
substantial progress has been made in 2D object part segmentation, the 3D counterpart has …
substantial progress has been made in 2D object part segmentation, the 3D counterpart has …
Semi-supervised 3D shape segmentation with multilevel consistency and part substitution
The lack of fine-grained 3D shape segmentation data is the main obstacle to develo**
learning-based 3D segmentation techniques. We propose an effective semi-supervised …
learning-based 3D segmentation techniques. We propose an effective semi-supervised …
MvDeCor: Multi-view Dense Correspondence Learning for Fine-Grained 3D Segmentation
We propose to utilize self-supervised techniques in the 2D domain for fine-grained 3D
shape segmentation tasks. This is inspired by the observation that view-based surface …
shape segmentation tasks. This is inspired by the observation that view-based surface …
One sketch for all: One-shot personalized sketch segmentation
We present the first one-shot personalized sketch segmentation method. We aim to segment
all sketches belonging to the same category provisioned with a single sketch with a given …
all sketches belonging to the same category provisioned with a single sketch with a given …
SCMS-Net: Self-supervised clustering-based 3D meshes segmentation network
The superior performance of deep learning in different domains has sparked significant
interest in its applicability to 3D computer graphics. Deep learning has become the dominant …
interest in its applicability to 3D computer graphics. Deep learning has become the dominant …
Few-shot multi-view object classification via dual augmentation network
Existing multi-view object classification algorithms usually rely on sufficient labeled multi-
view objects, which substantially restricts their scalability to novel classes with few annotated …
view objects, which substantially restricts their scalability to novel classes with few annotated …