Learning deep networks for video object segmentation
The Segment Anything Model (SAM) is an image segmentation model which has gained significant traction due to its powerful zero shot transfer performance on unseen data distributions as well as application to downstream tasks. It has a broad support of input methods such as point, box, and automa...
Saved in:
Main Author: | Lim, Jun Rong |
---|---|
Other Authors: | Lin Guosheng |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/175018 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Integrated segmentation approach for video coding
by: Swain C.T., et al.
Published: (2018) -
Guided Co-segmentation network for fast video object segmentation
by: Liu, Weide, et al.
Published: (2021) -
Recent advances in deep learning for object detection
by: WU, Xiongwei, et al.
Published: (2020) -
Delving deep into many-to-many attention for few-shot video object segmentation
by: CHEN, Haoxin, et al.
Published: (2021) -
Segmenting and tracking objects in video sequences based on graphical probabilistic models
by: WANG YANG
Published: (2010)