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Models/LETR

LETR

Reported on 9 benchmarks across 3 tasks · 1 paper · 9 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology6 results

Transfer Learningonwireframe dataset
FH· 2021-01-06
83.3
SOTA
Line Segment Detection Using Transformers without Edges arXiv:2101.01909
Transfer Learningonwireframe dataset
sAP10· 2021-01-06
65.2
SOTA
Line Segment Detection Using Transformers without Edges arXiv:2101.01909
Transfer Learningonwireframe dataset
sAP15· 2021-01-06
67.7
SOTA
Line Segment Detection Using Transformers without Edges arXiv:2101.01909
Multi-Task Learningonwireframe dataset
FH· 2021-01-06
83.3
SOTA
Line Segment Detection Using Transformers without Edges arXiv:2101.01909
Multi-Task Learningonwireframe dataset
sAP10· 2021-01-06
65.2
SOTA
Line Segment Detection Using Transformers without Edges arXiv:2101.01909
Multi-Task Learningonwireframe dataset
sAP15· 2021-01-06
67.7
SOTA
Line Segment Detection Using Transformers without Edges arXiv:2101.01909

Computer Vision3 results

Line Segment DetectiononYork Urban Dataset
FH· uses extra data· 2021-01-06
66.9
SOTA
Line Segment Detection Using Transformers without Edges arXiv:2101.01909
Line Segment DetectiononYork Urban Dataset
sAP10· uses extra data· 2021-01-06
29.4
best: 34.9 (LINEA-L)
SOTA
Line Segment Detection Using Transformers without Edges arXiv:2101.01909
Line Segment DetectiononYork Urban Dataset
sAP15· uses extra data· 2021-01-06
31.7
best: 37.3 (LINEA-L)
SOTA
Line Segment Detection Using Transformers without Edges arXiv:2101.01909