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2D Classification

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코드

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

https://github.com/NM-Streamlit-Team/meditools

공식 코드

MediTools -- Medical Education Powered by LLMs

https://github.com/NUAAXQ/MLCVNet

공식 코드

MLCVNet: Multi-Level Context VoteNet for 3D Object Detection

https://github.com/NUST-Machine-Intelligence-Laboratory/HFAN

공식 코드

Hierarchical Feature Alignment Network for Unsupervised Video Object Segmentation

https://github.com/NVIDIA/FastPhotoStyle

공식 코드

A Closed-form Solution to Photorealistic Image Stylization

https://github.com/NVIDIA/flowtron

공식 코드

Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis

https://github.com/NVlabs/BundleSDF

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BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects

https://github.com/NVlabs/CF-3DGS

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COLMAP-Free 3D Gaussian Splatting

https://github.com/NVlabs/CenterPose

공식 코드

Single-Stage Keypoint-Based Category-Level Object Pose Estimation from an RGB Image

https://github.com/NVlabs/DICOD

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Distilling Image Classifiers in Object Detectors

https://github.com/NVlabs/FasterViT

공식 코드

FasterViT: Fast Vision Transformers with Hierarchical Attention

https://github.com/NVlabs/FocalFormer3D

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FocalFormer3D : Focusing on Hard Instance for 3D Object Detection

https://github.com/NVlabs/FoundationStereo

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FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objects

https://github.com/NVlabs/GroupViT

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GroupViT: Semantic Segmentation Emerges from Text Supervision

https://github.com/NVlabs/condensa

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A Programmable Approach to Neural Network Compression

https://github.com/NVlabs/eg3d

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Efficient Geometry-aware 3D Generative Adversarial Networks

https://github.com/NVlabs/neuralangelo

공식 코드

Neuralangelo: High-Fidelity Neural Surface Reconstruction

https://github.com/NVlabs/wetectron

공식 코드

Instance-aware, Context-focused, and Memory-efficient Weakly Supervised Object Detection

https://github.com/Na-Z/sess

공식 코드

SESS: Self-Ensembling Semi-Supervised 3D Object Detection

https://github.com/NathanUA/BASNet

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Boundary-Aware Segmentation Network for Mobile and Web Applications

https://github.com/NathanUA/U-2-Net

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U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection

https://github.com/NatiOfir/SuperPixelFusion

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Multispectral image fusion based on super pixel segmentation

https://github.com/Natlem/M-HTCN

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Incremental Multi-Target Domain Adaptation for Object Detection with Efficient Domain Transfer

https://github.com/NervanaSystems/distiller

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Improving Neural Network Quantization without Retraining using Outlier Channel Splitting

https://github.com/NesterukSergey/segmentation_image_augmentation

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Image Augmentation for Multitask Few-Shot Learning: Agricultural Domain Use-Case

https://github.com/NeurAI-Lab/UniNet

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UniNet: A Unified Scene Understanding Network and Exploring Multi-Task Relationships through the Lens of Adversarial Attacks

https://github.com/NeuralSec/Daedalus-attack

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Daedalus: Breaking Non-Maximum Suppression in Object Detection via Adversarial Examples

https://github.com/NeuromorphicComputing/S-TEC

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Self-Supervised Learning Through Efference Copies

https://github.com/NevSNev/UniST

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Two Birds, One Stone: A Unified Framework for Joint Learning of Image and Video Style Transfers

https://github.com/Nightmare-n/UniPAD

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UniPAD: A Universal Pre-training Paradigm for Autonomous Driving

https://github.com/Noahs-ARK/idea_relations

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Friendships, Rivalries, and Trysts: Characterizing Relations between Ideas in Texts

https://github.com/NorskRegnesentral/weak-supervision-for-NER

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Named Entity Recognition without Labelled Data: A Weak Supervision Approach

https://github.com/OAfzal/nlp-for-peer-review

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What Can Natural Language Processing Do for Peer Review?

https://github.com/OIPLab-DUT/CoNet

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Accurate RGB-D Salient Object Detection via Collaborative Learning

https://github.com/OPIXray-author/OPIXray

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Occluded Prohibited Items Detection: an X-ray Security Inspection Benchmark and De-occlusion Attention Module

https://github.com/OUCVisionGroup/TISC-Net

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Towards the in-situ Trunk Identification and Length Measurement of Sea Cucumbers via Bézier Curve Modelling

https://github.com/OVAD-Benchmark/ovad-bechmark-code

공식 코드

Open-vocabulary Attribute Detection

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