← Semi-Supervised Semantic Segmentation
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SemanticKITTI

아카이브 평가 12건 · 마지막 적재/변경

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과거 수집 기록이며 최신 순위가 아닙니다. 데이터셋 버전·split·실험 조건과 지표 방향이 검증되지 않은 결과는 직접 비교할 수 없습니다. 날짜는 논문 날짜이며 최신 평가일을 뜻하지 않습니다.

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원본 기록 순서 · 순위 미부여
모델원본 지표·값논문구현
PLE (Voxel)
mIoU (1% Labels)
61.1
mIoU (10% Labels)
63.1
mIoU (20% Labels)
64.1
mIoU (50% Labels)
64.3
mIoU (0.5% Labels)
52.2
mIoU (2% Labels)
62.9
mIoU (5% Labels)
62.8
Learning from Spatio-temporal Correlation for Semi-Supervised LiDAR Semantic Segmentation
2024-10-09
코드 1
LaserMix (Voxel)
mIoU (0.5% Labels)
47.3
mIoU (2% Labels)
59.2
mIoU (5% Labels)
61.7
Learning from Spatio-temporal Correlation for Semi-Supervised LiDAR Semantic Segmentation
2024-10-09
코드 1
PLE (CENet, Range view)
mIoU (1% Labels)
51.5
mIoU (0.5% Labels)
46.2
mIoU (2% Labels)
54.3
mIoU (5% Labels)
58.1
Learning from Spatio-temporal Correlation for Semi-Supervised LiDAR Semantic Segmentation
2024-10-09
코드 1
360° from a Single Camera: A Few-Shot Approach for LiDAR Segmentation (All)
mIoU (1% Labels)
59.5
mIoU (10% Labels)
62.4
mIoU (20% Labels)
64.2
mIoU (50% Labels)
66.1
mIOU (1% Test set)
57.7
360$^\circ$ from a Single Camera: A Few-Shot Approach for LiDAR Segmentation
2023-09-12
연결 없음
SAPCA (Cylinder3D)
mIoU (1% Labels)
50.9
mIoU (10% Labels)
64.0
mIoU (50% Labels)
64.9
What Can be Seen is What You Get: Structure Aware Point Cloud Augmentation
2022-06-20
연결 없음
LaserMix (Voxel)
mIoU (1% Labels)
50.6
mIoU (10% Labels)
60.0
mIoU (20% Labels)
61.9
mIoU (50% Labels)
62.3
LaserMix for Semi-Supervised LiDAR Semantic Segmentation
2022-06-30
코드 1 · 코드 2
MeanTeacher (Voxel)
mIoU (1% Labels)
45.4
mIoU (10% Labels)
57.1
mIoU (20% Labels)
59.2
mIoU (50% Labels)
60.0
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
2017-03-06
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8
LaserMix (Range View)
mIoU (1% Labels)
43.4
mIoU (10% Labels)
58.8
mIoU (20% Labels)
59.4
mIoU (50% Labels)
61.4
LaserMix for Semi-Supervised LiDAR Semantic Segmentation
2022-06-30
코드 1 · 코드 2
CBST (Range View)
mIoU (1% Labels)
39.9
mIoU (10% Labels)
53.4
mIoU (20% Labels)
56.1
mIoU (50% Labels)
56.9
Unsupervised Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training
2018-09-01
코드 1
MeanTeacher (Range View)
mIoU (1% Labels)
37.5
mIoU (10% Labels)
53.1
mIoU (20% Labels)
56.1
mIoU (50% Labels)
57.4
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
2017-03-06
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8
CutMix-Seg (Range View)
mIoU (1% Labels)
37.4
mIoU (10% Labels)
54.3
mIoU (20% Labels)
56.6
mIoU (50% Labels)
57.6
Semi-supervised semantic segmentation needs strong, varied perturbations
2019-06-05
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5
CPS (Range View)
mIoU (1% Labels)
36.5
mIoU (10% Labels)
52.3
mIoU (20% Labels)
56.3
mIoU (50% Labels)
57.4
Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision
2021-06-02
코드 1 · 코드 2 · 코드 3