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Boundary Detection

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하위 태스크: 1
평가표: 8
보존된 평가 기록: 20

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

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/frednam93/JiTTER-SED

공식 코드

JiTTER: Jigsaw Temporal Transformer for Event Reconstruction for Self-Supervised Sound Event Detection

https://github.com/gaozhangyang/DGC

공식 코드

Clustering Based on Graph of Density Topology

https://github.com/genaios/textmachina

공식 코드

TextMachina: Seamless Generation of Machine-Generated Text Datasets

https://github.com/geoffroypeeters/ssmnet_ISMIR2023

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Self-Similarity-Based and Novelty-based loss for music structure analysis

https://github.com/giaracvi/NEFCI

공식 코드

Neuro-inspired edge feature fusion using Choquet integrals

https://github.com/guo-research-group/ct-bound

공식 코드

CT-Bound: Robust Boundary Detection From Noisy Images Via Hybrid Convolution and Transformer Neural Networks

https://github.com/gx77/lcvsl

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Local Compressed Video Stream Learning for Generic Event Boundary Detection

https://github.com/haruishi43/boundary_boost_mmseg

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Boosting Semantic Segmentation with Semantic Boundaries

https://github.com/hello-jinwoo/LOVEU-CVPR2021

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Winning the CVPR'2021 Kinetics-GEBD Challenge: Contrastive Learning Approach

https://github.com/hirofumi0810/neural_sp

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Enhancing Monotonic Multihead Attention for Streaming ASR

https://github.com/hmarichal93/cstrd_ipol

공식 코드

CS-TRD: a Cross Sections Tree Ring Detection method

https://github.com/hmarichal93/mlbrief_inbd

공식 코드

A Brief Analysis of the Iterative Next Boundary Detection Network for Tree Rings Delineation in Images of Pinus taeda

https://github.com/hmarichal93/uruDendro

공식 코드

UruDendro, a public dataset of cross-section images of Pinus taeda

https://github.com/huangkuns/wireframe

공식 코드

Learning to Parse Wireframes in Images of Man-Made Environments

https://github.com/huspacy/huspacy

공식 코드

Advancing Hungarian Text Processing with HuSpaCy: Efficient and Accurate NLP Pipelines

https://github.com/innovator-zero/MTDP_Lib

공식 코드

Prompt Guided Transformer for Multi-Task Dense Prediction

https://github.com/karlstratos/mention2vec

공식 코드

Entity Identification as Multitasking

https://github.com/knowledgeresearch/kaner

공식 코드

Rethinking the Value of Gazetteer in Chinese Named Entity Recognition

https://github.com/liuzywen/cod

공식 코드

Boosting Camouflaged Object Detection with Dual-Task Interactive Transformer

https://github.com/lkeab/BCNet

공식 코드

Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers

https://github.com/lufficc/sc-transformer

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SC-Transformer++: Structured Context Transformer for Generic Event Boundary Detection

https://github.com/mahaoxiang822/boundary-guided-context-aggregation

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Boundary Guided Context Aggregation for Semantic Segmentation

https://github.com/mcg-nju/ddm

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Progressive Attention on Multi-Level Dense Difference Maps for Generic Event Boundary Detection

https://github.com/melgharib/DSBD

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Large-scale, Fast and Accurate Shot Boundary Detection through Spatio-temporal Convolutional Neural Networks

https://github.com/microsoft/TableSense

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TableSense: Spreadsheet Table Detection with Convolutional Neural Networks

https://github.com/mikeadamer/mag-metric

공식 코드

The magnitude vector of images

https://github.com/natriistorm/semeval2024-boundary-detection

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DeepPavlov at SemEval-2024 Task 8: Leveraging Transfer Learning for Detecting Boundaries of Machine-Generated Texts

https://github.com/ns-moosavi/coval

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Using Automatically Extracted Minimum Spans to Disentangle Coreference Evaluation from Boundary Detection

https://github.com/palmtreemodel/palmtree

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PalmTree: Learning an Assembly Language Model for Instruction Embedding

https://github.com/prismformore/InvPT

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InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene Understanding

https://github.com/punk95/continual-learning-with-curiosity

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Using Curiosity for an Even Representation of Tasks in Continual Offline Reinforcement Learning

https://github.com/rayush7/motion_ssl_gebd

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Motion Aware Self-Supervision for Generic Event Boundary Detection

https://github.com/robot-learning-freiburg/PASTEL

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A Good Foundation is Worth Many Labels: Label-Efficient Panoptic Segmentation

https://github.com/s9xie/hed

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Holistically-Nested Edge Detection

https://github.com/saadwazir/HistoSeg

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HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images

https://github.com/saali14/Scan-to-BRep

공식 코드

BRep Boundary and Junction Detection for CAD Reverse Engineering

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.