Papers with Code 아카이브

3D Reconstruction

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하위 태스크: 7
평가표: 10
보존된 평가 기록: 44

3D Reconstruction is the task of creating a 3D model or representation of an object or scene from 2D images or other data sources. The goal of 3D reconstruction is to create a virtual representation of an object or scene that can be used for a variety of purposes, such as visualization, animation, simulation, and analysis. It can be used in fields such as computer vision, robotics, and virtual reality.

Image: Gwak et al

코드

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

https://github.com/dqj5182/contho_release

공식 코드

Joint Reconstruction of 3D Human and Object via Contact-Based Refinement Transformer

https://github.com/dreamguo/UNIKD

공식 코드

UNIKD: UNcertainty-filtered Incremental Knowledge Distillation for Neural Implicit Representation

https://github.com/ds4dm/CAPsac

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The Covering-Assignment Problem for Swarm-powered Ad-hoc Clouds: A Distributed 3D Mapping Use-case

https://github.com/dsvilarkovic/dynamic_plane_convolutional_onet

공식 코드

Dynamic Plane Convolutional Occupancy Networks

https://github.com/dtc111111/mcnslam

공식 코드

MCN-SLAM: Multi-Agent Collaborative Neural SLAM with Hybrid Implicit Neural Scene Representation

https://github.com/dtc111111/neslam

공식 코드

NeSLAM: Neural Implicit Mapping and Self-Supervised Feature Tracking With Depth Completion and Denoising

https://github.com/ductuantruong/tcm_add

공식 코드

Temporal-Channel Modeling in Multi-head Self-Attention for Synthetic Speech Detection

https://github.com/eckertzhang/text2nerf

공식 코드

Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fields

https://github.com/ellimac0/sat-ngp

공식 코드

SAT-NGP : Unleashing Neural Graphics Primitives for Fast Relightable Transient-Free 3D reconstruction from Satellite Imagery

https://github.com/emmamost26/CamSceneRegistration

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Acquiring Submillimeter-Accurate Multi-Task Vision Datasets for Computer-Assisted Orthopedic Surgery

https://github.com/enriccorona/SMPLicit

공식 코드

SMPLicit: Topology-aware Generative Model for Clothed People

https://github.com/enyu-liu/disc

공식 코드

Disentangling Instance and Scene Contexts for 3D Semantic Scene Completion

https://github.com/epsilon404/surgicalnerf

공식 코드

A Review of 3D Reconstruction Techniques for Deformable Tissues in Robotic Surgery

https://github.com/ericshenggle/LineGS

공식 코드

LineGS : 3D Line Segment Representation on 3D Gaussian Splatting

https://github.com/eriksandstroem/splat-slam

공식 코드

Splat-SLAM: Globally Optimized RGB-only SLAM with 3D Gaussians

https://github.com/erprogs/CViT

공식 코드

Deepfake Video Detection Using Convolutional Vision Transformer

https://github.com/erprogs/genconvit

공식 코드

Deepfake Video Detection Using Generative Convolutional Vision Transformer

https://github.com/esizikova/medsynth_public

공식 코드

Improving Computed Tomography (CT) Reconstruction via 3D Shape Induction

https://github.com/esw0116/odgs

공식 코드

ODGS: 3D Scene Reconstruction from Omnidirectional Images with 3D Gaussian Splattings

https://github.com/ethz-asl/kalibr

공식 코드

The Double Sphere Camera Model

https://github.com/ethz-asl/mav_active_3d_planning

공식 코드

An Efficient Sampling-based Method for Online Informative Path Planning in Unknown Environments

https://github.com/ethz-asl/neuralblox

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NeuralBlox: Real-Time Neural Representation Fusion for Robust Volumetric Mapping

https://github.com/eurecom-asp/rawgat-st-antispoofing

공식 코드

End-to-End Spectro-Temporal Graph Attention Networks for Speaker Verification Anti-Spoofing and Speech Deepfake Detection

https://github.com/eurecom-asp/rawnet2-antispoofing

공식 코드

End-to-end anti-spoofing with RawNet2

https://github.com/eurecom-fscv/2d-malafide

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2D-Malafide: Adversarial Attacks Against Face Deepfake Detection Systems

https://github.com/ewrfcas/mvsformer

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MVSFormer: Multi-View Stereo by Learning Robust Image Features and Temperature-based Depth

https://github.com/fabiopoiesi/4dm

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Multi-view data capture for dynamic object reconstruction using handheld augmented reality mobiles

https://github.com/face3d0725/FaceExtraction

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FaceOcc: A Diverse, High-quality Face Occlusion Dataset for Human Face Extraction

https://github.com/facebookresearch/Active-3D-Vision-and-Touch

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Active 3D Shape Reconstruction from Vision and Touch

https://github.com/facebookresearch/AnimalAvatar

공식 코드

Animal Avatars: Reconstructing Animatable 3D Animals from Casual Videos

https://github.com/facebookresearch/TemporallyConsistentDepth

공식 코드

Temporally Consistent Online Depth Estimation Using Point-Based Fusion

https://github.com/facebookresearch/banmo

공식 코드

BANMo: Building Animatable 3D Neural Models from Many Casual Videos

https://github.com/facebookresearch/c3dm

공식 코드

Canonical 3D Deformer Maps: Unifying parametric and non-parametric methods for dense weakly-supervised category reconstruction

https://github.com/facebookresearch/co3d

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Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction

https://github.com/facebookresearch/efm3d

공식 코드

EFM3D: A Benchmark for Measuring Progress Towards 3D Egocentric Foundation Models

https://github.com/facebookresearch/egolifter

공식 코드

EgoLifter: Open-world 3D Segmentation for Egocentric Perception

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