Semantic scene completion with cleaner self
Semantic Scene Completion (SSC) transforms an image of single-view depth and/or RGB 2D pixels into 3D voxels, each of whose semantic labels are predicted. SSC is a well-known ill-posed problem as the prediction model has to “imagine” what is behind the visible surface, which is usually represented b...
Saved in:
Main Authors: | WANG, Fengyun, ZHANG, Dong, ZHANG, Hanwang, TANG, Jinhui, SUN, Qianru |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2023
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/8100 https://ink.library.smu.edu.sg/context/sis_research/article/9103/viewcontent/Wang_Semantic_Scene_Completion_With_Cleaner_Self_CVPR_2023_paper.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Self-regulation for semantic segmentation
by: ZHANG, Dong, et al.
Published: (2021) -
Self-supervised learning disentangled group representation as feature
by: WANG, Tan, et al.
Published: (2021) -
Visual commonsense representation learning via causal inference
by: WANG, Tan, et al.
Published: (2020) -
Are missing links predictable? An inferential benchmark for knowledge graph completion
by: CAO, Yixin, et al.
Published: (2021) -
Compositional prompt tuning with motion cues for open-vocabulary video relation detection
by: GAO, Kaifeng, et al.
Published: (2023)