A comprehensive review of modern object segmentation approaches
Image segmentation is the task of associating pixels in an image with their respective object
class labels. It has a wide range of applications in many industries including healthcare …
class labels. It has a wide range of applications in many industries including healthcare …
Segmenting objects from relational visual data
In this article, we model a set of pixelwise object segmentation tasks—automatic video
segmentation (AVS), image co-segmentation (ICS) and few-shot semantic segmentation …
segmentation (AVS), image co-segmentation (ICS) and few-shot semantic segmentation …
A survey on deep learning technique for video segmentation
Video segmentation—partitioning video frames into multiple segments or objects—plays a
critical role in a broad range of practical applications, from enhancing visual effects in movie …
critical role in a broad range of practical applications, from enhancing visual effects in movie …
[HTML][HTML] On the use of deep learning for video classification
The video classification task has gained significant success in the recent years. Specifically,
the topic has gained more attention after the emergence of deep learning models as a …
the topic has gained more attention after the emergence of deep learning models as a …
Hierarchical feature alignment network for unsupervised video object segmentation
Optical flow is an easily conceived and precious cue for advancing unsupervised video
object segmentation (UVOS). Most of the previous methods directly extract and fuse the …
object segmentation (UVOS). Most of the previous methods directly extract and fuse the …
A unified transformer framework for group-based segmentation: Co-segmentation, co-saliency detection and video salient object detection
Humans tend to mine objects by learning from a group of images or several frames of video
since we live in a dynamic world. In the computer vision area, many researchers focus on co …
since we live in a dynamic world. In the computer vision area, many researchers focus on co …
Reciprocal transformations for unsupervised video object segmentation
Unsupervised video object segmentation (UVOS) aims at segmenting the primary objects in
videos without any human intervention. Due to the lack of prior knowledge about the primary …
videos without any human intervention. Due to the lack of prior knowledge about the primary …
Deep transport network for unsupervised video object segmentation
The popular unsupervised video object segmentation methods fuse the RGB frame and
optical flow via a two-stream network. However, they cannot handle the distracting noises in …
optical flow via a two-stream network. However, they cannot handle the distracting noises in …
Treating motion as option to reduce motion dependency in unsupervised video object segmentation
Unsupervised video object segmentation (VOS) aims to detect the most salient object in a
video sequence at the pixel level. In unsupervised VOS, most state-of-the-art methods …
video sequence at the pixel level. In unsupervised VOS, most state-of-the-art methods …
Learning motion-appearance co-attention for zero-shot video object segmentation
How to make the appearance and motion information interact effectively to accommodate
complex scenarios is a fundamental issue in flow-based zero-shot video object …
complex scenarios is a fundamental issue in flow-based zero-shot video object …