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2D Classification

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

https://github.com/DianaNerualNetwork/StainPromptInversion

공식 코드

Unpaired Multi-Domain Histopathology Virtual Staining using Dual Path Prompted Inversion

https://github.com/DiegoKoz/scisci

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Semantic and Relational Spaces in Science of Science: Deep Learning Models for Article Vectorisation

https://github.com/DingXiaoH/DiverseBranchBlock

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Diverse Branch Block: Building a Convolution as an Inception-like Unit

https://github.com/Dishant-P/S-Extension-patch-Official-research-module

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S-Extension Patch: A simple and efficient way to extend an object detection model

https://github.com/Div99/W-Stereo-Disp

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Wasserstein Distances for Stereo Disparity Estimation

https://github.com/Divadi/MTC_RCNN

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Multi-Modality Task Cascade for 3D Object Detection

https://github.com/DmitryUlyanov/texture_nets

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Texture Networks: Feed-forward Synthesis of Textures and Stylized Images

https://github.com/DoctorKey/LSHFM.detection

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Distilling Knowledge by Mimicking Features

https://github.com/DoctorKey/LSHFM.multiclassification

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Distilling Knowledge by Mimicking Features

https://github.com/DoctorKey/LSHFM.singleclassification

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Distilling Knowledge by Mimicking Features

https://github.com/Dod-o/VT-SSum

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VT-SSum: A Benchmark Dataset for Video Transcript Segmentation and Summarization

https://github.com/Don767/segdet_mlcr2024

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Replication Study and Benchmarking of Real-Time Object Detection Models

https://github.com/Dong-Huo/ASPDC

공식 코드

Blind Non-Uniform Motion Deblurring using Atrous Spatial Pyramid Deformable Convolution and Deblurring-Reblurring Consistency

https://github.com/DongSky/lbba_boosted_wsod

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Boosting Weakly Supervised Object Detection via Learning Bounding Box Adjusters

https://github.com/Duankaiwen/CPNDet

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Corner Proposal Network for Anchor-free, Two-stage Object Detection

https://github.com/Duankaiwen/CenterNet

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CenterNet: Keypoint Triplets for Object Detection

https://github.com/Duankaiwen/LSNet

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Location-Sensitive Visual Recognition with Cross-IOU Loss

https://github.com/Duankaiwen/PyCenterNet

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CenterNet++ for Object Detection

https://github.com/Dwrety/mmdetection-selective-iou

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Solving Missing-Annotation Object Detection with Background Recalibration Loss

https://github.com/EMI-Group/RelativeNAS

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RelativeNAS: Relative Neural Architecture Search via Slow-Fast Learning

https://github.com/ENSTA-U2IS-AI/Multimodal_Deep_segmentation

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InfraParis: A multi-modal and multi-task autonomous driving dataset

https://github.com/ENSTA-U2IS-AI/torch-uncertainty

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MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for multiple uncertainty types and tasks

https://github.com/EPFL-VILAB/XTConsistency

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Robust Learning Through Cross-Task Consistency

https://github.com/ESA-Datalabs/llm-usage-astronomy

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Delving into the Utilisation of ChatGPT in Scientific Publications in Astronomy

https://github.com/ETHRuiGong/DLOW

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DLOW: Domain Flow for Adaptation and Generalization

https://github.com/Eaphan/GLENet

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GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty Estimation

https://github.com/Eaphan/Robust3DOD

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A Comprehensive Study of the Robustness for LiDAR-based 3D Object Detectors against Adversarial Attacks

https://github.com/EdinburghNLP/csi-corpus

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Screenplay Summarization Using Latent Narrative Structure

https://github.com/EducationalTestingService/discourse-parsing

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Fast Rhetorical Structure Theory Discourse Parsing

https://github.com/EhsanBitaraf/dataset-mie-literature

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Decoding MIE: A Novel Dataset Approach Using Topic Extraction and Affiliation Parsing

https://github.com/Eisbaer8/DeepGTAV

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Leveraging Synthetic Data in Object Detection on Unmanned Aerial Vehicles

https://github.com/Elbria/ST-human-review

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A Review of Human Evaluation for Style Transfer

https://github.com/Elbria/xformal-FoST

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XFORMAL: A Benchmark for Multilingual Formality Style Transfer

https://github.com/Eli-YiLi/ScaleNet

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Data-Driven Neuron Allocation for Scale Aggregation Networks

https://github.com/EncryptedBinary/Meta_analysis

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Empowering Meta-Analysis: Leveraging Large Language Models for Scientific Synthesis

https://github.com/EndyWon/Deep-Feature-Perturbation

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Diversified Arbitrary Style Transfer via Deep Feature Perturbation

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