Boundary Detection
99 papers with code • 3 benchmarks • 10 datasets
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
Benchmarks
These leaderboards are used to track progress in Boundary Detection
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Libraries
Use these libraries to find Boundary Detection models and implementationsDatasets
Kinetics
NYUv2
Kinetics 400
PASCAL Context
SoccerNet-v2
UruDendro
CaFFe
Oxford Road Boundaries
Latest papers with no code
TM-TREK at SemEval-2024 Task 8: Towards LLM-Based Automatic Boundary Detection for Human-Machine Mixed Text
With the increasing prevalence of text generated by large language models (LLMs), there is a growing concern about distinguishing between LLM-generated and human-written texts in order to prevent the misuse of LLMs, such as the dissemination of misleading information and academic dishonesty.
A Transformer Model for Boundary Detection in Continuous Sign Language
One of the prominent challenges in CSLR pertains to accurately detecting the boundaries of isolated signs within a continuous video stream.
Segment Boundary Detection via Class Entropy Measurements in Connectionist Phoneme Recognition
The advantage of this measure is its simplicity as the posterior probabilities of each class are available in connectionist phoneme recognition.
EtC: Temporal Boundary Expand then Clarify for Weakly Supervised Video Grounding with Multimodal Large Language Model
To further clarify the noise of expanded boundaries, we combine mutual learning with a tailored proposal-level contrastive objective to use a learnable approach to harmonize a balance between incomplete yet clean (initial) and comprehensive yet noisy (expanded) boundaries for more precise ones.
AI-generated text boundary detection with RoFT
Due to the rapid development of large language models, people increasingly often encounter texts that may start as written by a human but continue as machine-generated.
Dealing with negative samples with multi-task learning on span-based joint entity-relation extraction
These models treat text spans as candidate entities, and span pairs as candidate relationship tuples, achieving state-of-the-art results on datasets like ADE.
Efficient Polyp Segmentation Via Integrity Learning
This paper introduces the integrity concept in polyp segmentation at both macro and micro levels, aiming to alleviate integrity deficiency.
Boundary-RL: Reinforcement Learning for Weakly-Supervised Prostate Segmentation in TRUS Images
We propose Boundary-RL, a novel weakly supervised segmentation method that utilises only patch-level labels for training.
The DKU-DUKEECE System for the Manipulation Region Location Task of ADD 2023
This paper introduces our system designed for Track 2, which focuses on locating manipulated regions, in the second Audio Deepfake Detection Challenge (ADD 2023).
Automatic Cadastral Boundary Detection of Very High Resolution Images Using Mask R-CNN
In this paper, we focus on deep learning and provide three geometric post-processing methods that improve the quality of the work.
