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

https://github.com/unity-technologies/peoplesanspeople

공식 코드

PeopleSansPeople: A Synthetic Data Generator for Human-Centric Computer Vision

https://github.com/univ-esuty/noisecollage

공식 코드

NoiseCollage: A Layout-Aware Text-to-Image Diffusion Model Based on Noise Cropping and Merging

https://github.com/unsigned-long/ekalibr

공식 코드

eKalibr: Dynamic Intrinsic Calibration for Event Cameras From First Principles of Events

https://github.com/ustclby/Unsupervised-Domain-Specific-Deblurring

공식 코드

Unsupervised Domain-Specific Deblurring via Disentangled Representations

https://github.com/usydnlp/VICTR

공식 코드

VICTR: Visual Information Captured Text Representation for Text-to-Image Multimodal Tasks

https://github.com/ut-vision/FgSty-CPL

공식 코드

Foreground-Aware Stylization and Consensus Pseudo-Labeling for Domain Adaptation of First-Person Hand Segmentation

https://github.com/ut-vision/s2dhand

공식 코드

Single-to-Dual-View Adaptation for Egocentric 3D Hand Pose Estimation

https://github.com/ut-vision/simhand

공식 코드

SiMHand: Mining Similar Hands for Large-Scale 3D Hand Pose Pre-training

https://github.com/utiasSTARS/bingham-rotation-learning

공식 코드

A Smooth Representation of Belief over SO(3) for Deep Rotation Learning with Uncertainty

https://github.com/uuembodiedsocialai/FaceDiffuser

공식 코드

FaceDiffuser: Speech-Driven 3D Facial Animation Synthesis Using Diffusion

https://github.com/uwaa-ndcl/pose_network_sensitivity

공식 코드

On the sensitivity of pose estimation neural networks: rotation parameterizations, Lipschitz constants, and provable bounds

https://github.com/uyoung-jeong/BoIR

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BoIR: Box-Supervised Instance Representation for Multi-Person Pose Estimation

https://github.com/uyoung-jeong/PoseBH

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PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation

https://github.com/uzh-rpg/hybrid_ann_snn

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A Hybrid ANN-SNN Architecture for Low-Power and Low-Latency Visual Perception

https://github.com/uzh-rpg/imips_open

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Matching Features without Descriptors: Implicitly Matched Interest Points

https://github.com/uzh-rpg/rpg_davis_simulator

공식 코드

The Event-Camera Dataset and Simulator: Event-based Data for Pose Estimation, Visual Odometry, and SLAM

https://github.com/uzh-rpg/sips2_open

공식 코드

SIPs: Succinct Interest Points from Unsupervised Inlierness Probability Learning

https://github.com/vaesl/IP-Net

공식 코드

Learning Human-Object Interaction Detection using Interaction Points

https://github.com/vagver/3dgazenet

공식 코드

3DGazeNet: Generalizing Gaze Estimation with Weak-Supervision from Synthetic Views

https://github.com/vagver/dense3deyes

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3DGazeNet: Generalizing Gaze Estimation with Weak-Supervision from Synthetic Views

https://github.com/vaibhav-khamankar/fusestyle

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Histopathological Image Analysis with Style-Augmented Feature Domain Mixing for Improved Generalization

https://github.com/vaibhavsaxena11/inverse-sigma-srn

공식 코드

Generalizable Pose Estimation Using Implicit Scene Representations

https://github.com/val-iisc/iSPA-Net

공식 코드

iSPA-Net: Iterative Semantic Pose Alignment Network

https://github.com/val-iisc/pose_estimation

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Object Pose Estimation from Monocular Image using Multi-View Keypoint Correspondence

https://github.com/val-iisc/sketch-parse

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SketchParse : Towards Rich Descriptions for Poorly Drawn Sketches using Multi-Task Hierarchical Deep Networks

https://github.com/val-iisc/ssl_3d_recon

공식 코드

From Image Collections to Point Clouds with Self-supervised Shape and Pose Networks

https://github.com/valentinkoch/svdna

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Noise transfer for unsupervised domain adaptation of retinal OCT images

https://github.com/valeoai/WoodScape/tree/master/omnidet

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OmniDet: Surround View Cameras based Multi-task Visual Perception Network for Autonomous Driving

https://github.com/valeoai/halton-maskgit

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Halton Scheduler For Masked Generative Image Transformer

https://github.com/valeoai/pafuse

공식 코드

PAFUSE: Part-based Diffusion for 3D Whole-Body Pose Estimation

https://github.com/vancyland/prompt-agnostic-adversarial-perturbation-for-customized-diffusion-models.github.io

공식 코드

Prompt-Agnostic Adversarial Perturbation for Customized Diffusion Models

https://github.com/vancyland/vancyland.github.io-project-PAP

공식 코드

Prompt-Agnostic Adversarial Perturbation for Customized Diffusion Models

https://github.com/vangiel/WheresTheFellow

공식 코드

Multi-camera Torso Pose Estimation using Graph Neural Networks

https://github.com/varunburde/reconstruction_pose_benchmark

공식 코드

Comparative Evaluation of 3D Reconstruction Methods for Object Pose Estimation

https://github.com/vastlik/symformer

공식 코드

SymFormer: End-to-end symbolic regression using transformer-based architecture

https://github.com/vb000/neuricam

공식 코드

NeuriCam: Key-Frame Video Super-Resolution and Colorization for IoT Cameras

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