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3D geometry

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

https://github.com/alvaro-budria/InstantGeoAvatar

공식 코드

InstantGeoAvatar: Effective Geometry and Appearance Modeling of Animatable Avatars from Monocular Video

https://github.com/angeladai/spsg

공식 코드

SPSG: Self-Supervised Photometric Scene Generation from RGB-D Scans

https://github.com/angtian/voge

공식 코드

VoGE: A Differentiable Volume Renderer using Gaussian Ellipsoids for Analysis-by-Synthesis

https://github.com/ant-research/scalelsd

공식 코드

ScaleLSD: Scalable Deep Line Segment Detection Streamlined

https://github.com/antonioo-c/geodrive

공식 코드

GeoDrive: 3D Geometry-Informed Driving World Model with Precise Action Control

https://github.com/apchenstu/sofgan

공식 코드

SofGAN: A Portrait Image Generator with Dynamic Styling

https://github.com/apple/ml-finerecon

공식 코드

FineRecon: Depth-aware Feed-forward Network for Detailed 3D Reconstruction

https://github.com/apple/ml-nvas3d

공식 코드

Novel-View Acoustic Synthesis from 3D Reconstructed Rooms

https://github.com/atomicarchitects/symphony

공식 코드

Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for 3D Molecule Generation

https://github.com/atomistic-machine-learning/G-SchNet

공식 코드

Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules

https://github.com/atrovast/thgs

공식 코드

Training-Free Hierarchical Scene Understanding for Gaussian Splatting with Superpoint Graphs

https://github.com/baaivision/See3D

공식 코드

You See it, You Got it: Learning 3D Creation on Pose-Free Videos at Scale

https://github.com/brjathu/T3DP

공식 코드

Tracking People with 3D Representations

https://github.com/callmeray/PointMVSNet

공식 코드

Point-Based Multi-View Stereo Network

https://github.com/cerf-volant425/thermal-nerf

공식 코드

Thermal-NeRF: Neural Radiance Fields from an Infrared Camera

https://github.com/chaitjo/geometric-rna-design

공식 코드

gRNAde: Geometric Deep Learning for 3D RNA inverse design

https://github.com/chao1224/graphmvp

공식 코드

Pre-training Molecular Graph Representation with 3D Geometry

https://github.com/chaoqi7/bsa-cil-3d

공식 코드

Boosting the Class-Incremental Learning in 3D Point Clouds via Zero-Collection-Cost Basic Shape Pre-Training

https://github.com/chenxuluo/EPC

공식 코드

Every Pixel Counts ++: Joint Learning of Geometry and Motion with 3D Holistic Understanding

https://github.com/chenyilun95/dsgn2

공식 코드

DSGN++: Exploiting Visual-Spatial Relation for Stereo-based 3D Detectors

https://github.com/concept-fusion/concept-fusion

공식 코드

ConceptFusion: Open-set Multimodal 3D Mapping

https://github.com/cskkxjk/mononerd

공식 코드

MonoNeRD: NeRF-like Representations for Monocular 3D Object Detection

https://github.com/cuteyyt/or-nerf

공식 코드

OR-NeRF: Object Removing from 3D Scenes Guided by Multiview Segmentation with Neural Radiance Fields

https://github.com/cvg/geocalib

공식 코드

GeoCalib: Learning Single-image Calibration with Geometric Optimization

https://github.com/cvg/pixloc

공식 코드

Back to the Feature: Learning Robust Camera Localization from Pixels to Pose

https://github.com/cvmi-lab/total-decom

공식 코드

Total-Decom: Decomposed 3D Scene Reconstruction with Minimal Interaction

https://github.com/czq142857/DECOR-GAN

공식 코드

DECOR-GAN: 3D Shape Detailization by Conditional Refinement

https://github.com/daniilidis-group/monocap

공식 코드

MonoCap: Monocular Human Motion Capture using a CNN Coupled with a Geometric Prior

https://github.com/deepmind/deepmind-research/tree/master/polygen

공식 코드

PolyGen: An Autoregressive Generative Model of 3D Meshes

https://github.com/defaultrui/vln-ver

공식 코드

Volumetric Environment Representation for Vision-Language Navigation

https://github.com/dingthuang/sd-net

공식 코드

SD-Net: Symmetric-Aware Keypoint Prediction and Domain Adaptation for 6D Pose Estimation In Bin-picking Scenarios

https://github.com/dwawayu/pensieve

공식 코드

Recollection from Pensieve: Novel View Synthesis via Learning from Uncalibrated Videos

https://github.com/enric1994/synth-colon

공식 코드

Synthetic data for unsupervised polyp segmentation

https://github.com/epic-kitchens/epic-fields-code

공식 코드

EPIC Fields: Marrying 3D Geometry and Video Understanding

https://github.com/er-muyue/bemapnet

공식 코드

End-to-End Vectorized HD-map Construction with Piecewise Bezier Curve

https://github.com/f3rm/f3rm

공식 코드

Distilled Feature Fields Enable Few-Shot Language-Guided Manipulation

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