SOTAVerified|Agents Browse Leaderboard About

Boundary Detection

Boundary Detection is a vital part of extracting information encoded in images, allowing for the computation of quantities of interest including density, velocity, pressure, etc.

Source: A Locally Adapting Technique for Boundary Detection using Image Segmentation

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 311–320 of 359 papers

Title	Date	Tasks	Status	Hype
CT-Bound: Robust Boundary Detection From Noisy Images Via Hybrid Convolution and Transformer Neural Networks	Mar 25, 2024	Boundary DetectionEdge Detection	CodeCode Available	0
Generic Event Boundary Detection in Video with Pyramid Features	Jan 11, 2023	Boundary DetectionDecoder	CodeCode Available	0
Rethinking the Value of Gazetteer in Chinese Named Entity Recognition	Jul 6, 2022	Boundary DetectionChinese Named Entity Recognition	CodeCode Available	0
MultiLegalSBD: A Multilingual Legal Sentence Boundary Detection Dataset	May 2, 2023	Boundary DetectionSentence	CodeCode Available	0
UberNet: Training a `Universal' Convolutional Neural Network for Low-, Mid-, and High-Level Vision using Diverse Datasets and Limited Memory	Sep 7, 2016	Boundary DetectionGPU	CodeCode Available	0
Ridiculously Fast Shot Boundary Detection with Fully Convolutional Neural Networks	May 23, 2017	Action RecognitionBoundary Detection	CodeCode Available	0
Guided learning for weakly-labeled semi-supervised sound event detection	Jun 6, 2019	Audio TaggingBoundary Detection	CodeCode Available	0
Boundary Detection and Categorization of Argument Aspects via Supervised Learning	Oct 1, 2022	Argument MiningBoundary Detection	CodeCode Available	0
Antarlekhaka: A Comprehensive Tool for Multi-task Natural Language Annotation	Oct 11, 2023	Boundary DetectionSentence	CodeCode Available	0
The Devil is in the Decoder: Classification, Regression and GANs	Jul 18, 2017	Boundary DetectionDecoder	CodeCode Available	0

Show:10 25 50

← PrevPage 32 of 36Next →

All datasets RoFT RoFT-chatgpt CoAuthor NYU-Depth V2 TriBERT (in-domain)UruDendro Kinetics 400 PASCAL Context

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	GigaCheck (DN-DAB-DETR)	Accuracy (%)	64.63	—	Unverified
2	RoBERTa + SEP	Accuracy (%)	49.64	—	Unverified
3	PHD + TS ML	Accuracy (%)	23.5	—	Unverified
4	TLE + TS Binary	Accuracy (%)	12.58	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GigaCheck (DN-DAB-DETR)	Accuracy (%)	67.65	—	Unverified
2	RoBERTa + SEP	Accuracy (%)	54.61	—	Unverified
3	TLE + TS Binary	Accuracy (%)	20.02	—	Unverified
4	PHD + TS ML	Accuracy (%)	17.29	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GigaCheck (Mistral-7B-v0.3)	Cohen’s Kappa score	0.42	—	Unverified
2	DeBERTa-v3 (Naive)	Cohen’s Kappa score	0.4	—	Unverified
3	GigaCheck (DN-DAB-DETR)	Cohen’s Kappa score	0.19	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	InvPT	odsF	78.1	—	Unverified
2	PGT (Swin-S)	odsF	78.04	—	Unverified
3	PGT (Swin-T)	odsF	77.05	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GigaCheck (DN-DAB-DETR)	F1@3	0.65	—	Unverified
2	TriBERT (p=2)	F1@3	0.58	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CS-TRD	Average Precision	0.94	—	Unverified
2	INBD	Average Precision	0.75	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CASTANET+ Ensemble	Pairwise F1	0.81	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	InvPT	odsF	73	—	Unverified