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코드

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

https://github.com/badripatro/mamba360

공식 코드

Mamba-360: Survey of State Space Models as Transformer Alternative for Long Sequence Modelling: Methods, Applications, and Challenges

https://github.com/bafanas/dlc-object-recognition-analysis

공식 코드

Exploring Novel Object Recognition and Spontaneous Location Recognition Machine Learning Analysis Techniques in Alzheimer's Mice

https://github.com/bahjat-kawar/snips_torch

공식 코드

SNIPS: Solving Noisy Inverse Problems Stochastically

https://github.com/bald6354/tore_volumes

공식 코드

Time-Ordered Recent Event (TORE) Volumes for Event Cameras

https://github.com/banafshebamdad/InCrowd-VI

공식 코드

InCrowd-VI: A Realistic Visual-Inertial Dataset for Evaluating SLAM in Indoor Pedestrian-Rich Spaces for Human Navigation

https://github.com/bandainamcoresearchinc/bandai-namco-research-motiondataset

공식 코드

Motion Capture Dataset for Practical Use of AI-based Motion Editing and Stylization

https://github.com/baniks/PoseGraphNet

공식 코드

3D Human Pose Regression using Graph Convolutional Network

https://github.com/baofff/U-ViT

공식 코드

All are Worth Words: A ViT Backbone for Diffusion Models

https://github.com/baoshengyu/H3R

공식 코드

Heatmap Regression via Randomized Rounding

https://github.com/bardhprenkaj/gist

공식 코드

Graph Style Transfer for Counterfactual Explainability

https://github.com/bardiadoosti/HOPE

공식 코드

HOPE-Net: A Graph-based Model for Hand-Object Pose Estimation

https://github.com/barisbatuhan/dass_det_inference

공식 코드

Domain-Adaptive Self-Supervised Pre-Training for Face & Body Detection in Drawings

https://github.com/barisbatuhan/dass_detector

공식 코드

Domain-Adaptive Self-Supervised Pre-Training for Face & Body Detection in Drawings

https://github.com/barisgecer/facegan

공식 코드

Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model

https://github.com/bastianwandt/CanonPose

공식 코드

CanonPose: Self-Supervised Monocular 3D Human Pose Estimation in the Wild

https://github.com/bbacic/tnwahi-appakrcs

공식 코드

Towards nation-wide analytical healthcare infrastructures: A privacy-preserving augmented knee rehabilitation case study

https://github.com/bbanar2/exploring_xai_in_genmus_via_lsr

공식 코드

Exploring XAI for the Arts: Explaining Latent Space in Generative Music

https://github.com/bbenligiray/stag

공식 코드

STag: A Stable Fiducial Marker System

https://github.com/bchimagine/real_time_fetal_brain_segmentation

공식 코드

Deep Learning Framework for Real-time Fetal Brain Segmentation in MRI

https://github.com/bcmi/DCI-VTON-Virtual-Try-On

공식 코드

Taming the Power of Diffusion Models for High-Quality Virtual Try-On with Appearance Flow

https://github.com/bcprescott/msds

공식 코드

COVID-19 Pneumonia and Influenza Pneumonia Detection Using Convolutional Neural Networks

https://github.com/bcv-uniandes/egocol

공식 코드

EgoCOL: Egocentric Camera pose estimation for Open-world 3D object Localization @Ego4D challenge 2023

https://github.com/bdvllrs/bimgw

공식 코드

Semi-supervised Multimodal Representation Learning through a Global Workspace

https://github.com/bearpaw/PyraNet

공식 코드

Learning Feature Pyramids for Human Pose Estimation

https://github.com/bebebe666/optimalsteps

공식 코드

Optimal Stepsize for Diffusion Sampling

https://github.com/behavioral-data/PARTNER

공식 코드

Towards Facilitating Empathic Conversations in Online Mental Health Support: A Reinforcement Learning Approach

https://github.com/beichenzbc/long-clip

공식 코드

Long-CLIP: Unlocking the Long-Text Capability of CLIP

https://github.com/benbillot/spatial_regularisation

공식 코드

Spatial regularisation for improved accuracy and interpretability in keypoint-based registration

https://github.com/benquick123/c-vton

공식 코드

C-VTON: Context-Driven Image-Based Virtual Try-On Network

https://github.com/berkeley-speech-group/speech-articulatory-coding

공식 코드

Coding Speech through Vocal Tract Kinematics

https://github.com/bgalerne/scaling_painting_style_transfer

공식 코드

Scaling Painting Style Transfer

https://github.com/bgu-cs-vil/timepoint

공식 코드

TimePoint: Accelerated Time Series Alignment via Self-Supervised Keypoint and Descriptor Learning

https://github.com/bidalab/improve

공식 코드

A multimodal dataset for understanding the impact of mobile phones on remote online virtual education

https://github.com/biggytruck/speechsplit2

공식 코드

SpeechSplit 2.0: Unsupervised speech disentanglement for voice conversion Without tuning autoencoder Bottlenecks

https://github.com/bigpon/vcc20_baseline_cyclevae

공식 코드

Baseline System of Voice Conversion Challenge 2020 with Cyclic Variational Autoencoder and Parallel WaveGAN

https://github.com/bigrayss/motion2vec

공식 코드

Dual-stream Transformer-GCN Model with Contextualized Representations Learning for Monocular 3D Human Pose Estimation

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