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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	Score
A Region-based Randers Geodesic Approach for Image Segmentation	Dec 20, 2019	Boundary DetectionImage Segmentation	—Unverified	0	0
Elephant: Sequence Labeling for Word and Sentence Segmentation	Oct 1, 2013	Boundary DetectionFeature Engineering	—Unverified	0	0
End-to-End Compressed Video Representation Learning for Generic Event Boundary Detection	Mar 29, 2022	Boundary DetectionGeneric Event Boundary Detection	—Unverified	0	0
English-French Document Alignment Based on Keywords and Statistical Translation	Aug 1, 2016	Boundary DetectionKeyword Extraction	—Unverified	0	0
Enhancing Answer Boundary Detection for Multilingual Machine Reading Comprehension	Apr 29, 2020	Boundary DetectionMachine Reading Comprehension	—Unverified	0	0
Entity Extraction in Biomedical Corpora: An Approach to Evaluate Word Embedding Features with PSO based Feature Selection	Apr 1, 2017	Boundary DetectionEntity Extraction using GAN	—Unverified	0	0
EtC: Temporal Boundary Expand then Clarify for Weakly Supervised Video Grounding with Multimodal Large Language Model	Dec 5, 2023	Boundary DetectionLanguage Modeling	—Unverified	0	0
Evaluating Word Embeddings for Sentence Boundary Detection in Speech Transcripts	Oct 1, 2017	Automatic Speech Recognition (ASR)Boundary Detection	—Unverified	0	0
Evaluating Word Embeddings for Sentence Boundary Detection in Speech Transcripts	Aug 15, 2017	Boundary DetectionSentence	—Unverified	0	0
EventVAD: Training-Free Event-Aware Video Anomaly Detection	Apr 17, 2025	Anomaly DetectionBoundary Detection	—Unverified	0	0

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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