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평가표

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보존된 평가 기록

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코드

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

https://github.com/tjiiv-cprg/epro-pnp

공식 코드

EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation

https://github.com/tjiiv-cprg/epro-pnp-v2

공식 코드

EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation

https://github.com/tldr-group/superres

공식 코드

Fusion of complementary 2D and 3D mesostructural datasets using generative adversarial networks

https://github.com/tlpss/workshop-icra-2022-cloth-keypoints

공식 코드

Learning Keypoints from Synthetic Data for Robotic Cloth Folding

https://github.com/tobibaum/partialsportsfieldreg_3dhpe

공식 코드

Monocular 3D Human Pose Estimation for Sports Broadcasts using Partial Sports Field Registration

https://github.com/tobran/DF-GAN

공식 코드

DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis

https://github.com/tobran/de-net

공식 코드

DE-Net: Dynamic Text-guided Image Editing Adversarial Networks

https://github.com/tobran/galip

공식 코드

GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis

https://github.com/toby-katakuri/lp_styletransfernet

공식 코드

Multiscale style transfer based on a Laplacian pyramid for traditional Chinese painting

https://github.com/tofis/human4d_dataset

공식 코드

HUMAN4D: A Human-Centric Multimodal Dataset for Motions and Immersive Media

https://github.com/tohinz/multiple-objects-gan

공식 코드

Generating Multiple Objects at Spatially Distinct Locations

https://github.com/tohinz/semantic-object-accuracy-for-generative-text-to-image-synthesis

공식 코드

Semantic Object Accuracy for Generative Text-to-Image Synthesis

https://github.com/tombs98/mhnet

공식 코드

Mixed Hierarchy Network for Image Restoration

https://github.com/tombs98/sfafnet

공식 코드

Spatial and Frequency Domain Adaptive Fusion Network for Image Deblurring

https://github.com/tommy-bie/mica

공식 코드

MICA: Towards Explainable Skin Lesion Diagnosis via Multi-Level Image-Concept Alignment

https://github.com/tomtirer/IDBP

공식 코드

Image Restoration by Iterative Denoising and Backward Projections

https://github.com/topo-epfl/crossloc

공식 코드

CrossLoc: Scalable Aerial Localization Assisted by Multimodal Synthetic Data

https://github.com/torchrwkv/flash-linear-attention

공식 코드

Cross-attention for State-based model RWKV-7

https://github.com/torrvision/spaint

공식 코드

Real-Time RGB-D Camera Pose Estimation in Novel Scenes using a Relocalisation Cascade

https://github.com/tothebeginning/pulid

공식 코드

PuLID: Pure and Lightning ID Customization via Contrastive Alignment

https://github.com/toughstonex/styledyrf

공식 코드

StyleDyRF: Zero-shot 4D Style Transfer for Dynamic Neural Radiance Fields

https://github.com/toytiny/milliflow

공식 코드

milliFlow: Scene Flow Estimation on mmWave Radar Point Cloud for Human Motion Sensing

https://github.com/tpark94/speedplusbaseline

공식 코드

SPEED+: Next-Generation Dataset for Spacecraft Pose Estimation across Domain Gap

https://github.com/tpark94/spnv2

공식 코드

Robust Multi-Task Learning and Online Refinement for Spacecraft Pose Estimation across Domain Gap

https://github.com/tpulkit/txt2vid

공식 코드

Txt2Vid: Ultra-Low Bitrate Compression of Talking-Head Videos via Text

https://github.com/tqtrunghnvn/SimMRPose

공식 코드

Simple Multi-Resolution Representation Learning for Human Pose Estimation

https://github.com/transpchan/Live3D

공식 코드

Collaborative Neural Rendering using Anime Character Sheets

https://github.com/travisdriver/spc-factor-results

공식 코드

Keypoint-based Stereophotoclinometry for Characterizing and Navigating Small Bodies: A Factor Graph Approach

https://github.com/trevorcanham/dcoupst

공식 코드

Using Decoupled Features for Photo-realistic Style Transfer

https://github.com/truongkhang/deviloc

공식 코드

Learning to Produce Semi-dense Correspondences for Visual Localization

https://github.com/tsattler/meshloc_release

공식 코드

MeshLoc: Mesh-Based Visual Localization

https://github.com/tsattler/understanding_apr

공식 코드

Understanding the Limitations of CNN-based Absolute Camera Pose Regression

https://github.com/tstafylakis/Speaker-Embeddings-Correlation-Pooling

공식 코드

Speaker embeddings by modeling channel-wise correlations

https://github.com/tsujuifu/pytorch_ldast

공식 코드

Language-Driven Image Style Transfer

https://github.com/tsunghan-wu/SLD

공식 코드

Self-correcting LLM-controlled Diffusion Models

https://github.com/ttchengab/continuous_3d_words_code

공식 코드

Learning Continuous 3D Words for Text-to-Image Generation

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