HyperAI
HyperAI초신경
홈
뉴스
최신 연구 논문
튜토리얼
데이터셋
백과사전
SOTA
LLM 모델
GPU 랭킹
컨퍼런스
전체 검색
소개
한국어
HyperAI
HyperAI초신경
Toggle sidebar
전체 사이트 검색...
⌘
K
홈
SOTA
반감독형 의미 분할
Semi Supervised Semantic Segmentation On 23
Semi Supervised Semantic Segmentation On 23
평가 지표
mIoU (1% Labels)
mIoU (10% Labels)
mIoU (20% Labels)
mIoU (50% Labels)
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
mIoU (1% Labels)
mIoU (10% Labels)
mIoU (20% Labels)
mIoU (50% Labels)
Paper Title
Repository
CutMix-Seg (Range View)
36.7
50.7
52.9
54.3
Semi-supervised semantic segmentation needs strong, varied perturbations
-
CBST (Range View)
35.7
50.7
52.7
54.6
Unsupervised Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training
Sup.-only (Voxel)
39.2
48.0
52.1
53.8
Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation
-
MeanTeacher (Range View)
34.2
49.8
51.6
53.3
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
-
LaserMix (Range View)
38.3
54.4
55.6
58.7
LaserMix for Semi-Supervised LiDAR Semantic Segmentation
-
MeanTeacher (Voxel)
41.0
50.1
52.8
53.9
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
-
CPS (Range View)
33.7
50.0
52.8
54.6
Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision
-
LaserMix (Voxel)
44.2
53.7
55.1
56.8
LaserMix for Semi-Supervised LiDAR Semantic Segmentation
-
Sup.-only (Range View)
33.1
47.7
49.9
52.5
FIDNet: LiDAR Point Cloud Semantic Segmentation with Fully Interpolation Decoding
-
0 of 9 row(s) selected.
Previous
Next
Semi Supervised Semantic Segmentation On 23 | SOTA | HyperAI초신경