[ICCV-23] Paper List - 3D

ICCV-23 paper list

目录

Oral Papers

3D from multi-view and sensors

Generative AI

Poster Papers

3D Generation (Neural generative models)

3D from a single image and shape-from-x

3D Editing

Face and gestures

Stylization

Dataset


Oral Papers

3D from multi-view and sensors

Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields

Tri-MipRF: Tri-Mip Representation for Efficient Anti-Aliasing Neural Radiance Fields

LERF: Language Embedded Radiance Fields

Mixed Neural Voxels for Fast Multi-view Video Synthesis

Multi-Modal Neural Radiance Field for Monocular Dense SLAM with a Light-Weight ToF Sensor

Diffusion-Guided Reconstruction of Everyday Hand-Object Interaction Clips

Instruct-NeRF2NeRF: Editing 3D Scenes with Instructions

Neural Haircut: Prior-Guided Strand-Based Hair Reconstruction

ScanNet++: A High-Fidelity Dataset of 3D Indoor Scenes

EgoLoc: Revisiting 3D Object Localization from Egocentric Videos with Visual Queries

Generative AI

TexFusion: Synthesizing 3D Textures with Text-Guided Image Diffusion Models

Generative Novel View Synthesis with 3D-Aware Diffusion Models

VQ3D: Learning a 3D-Aware Generative Model on ImageNet

Poster Papers

3D Generation (Neural generative models)

GRAM-HD: 3D-Consistent Image Generation at High Resolution with Generative Radiance Manifolds

Generative Multiplane Neural Radiance for 3D-Aware Image Generation

Get3DHuman: Lifting StyleGAN-Human into a 3D Generative Model Using Pixel-Aligned Reconstruction Priors

Towards High-Fidelity Text-Guided 3D Face Generation and Manipulation Using only Images

ATT3D: Amortized Text-to-3D Object Synthesis

Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creation

GETAvatar: Generative Textured Meshes for Animatable Human Avatars

Mimic3D: Thriving 3D-Aware GANs via 3D-to-2D Imitation

DreamBooth3D: Subject-Driven Text-to-3D Generation

3D-aware Image Generation using 2D Diffusion Models

Single-Stage Diffusion NeRF: A Unified Approach to 3D Generation and Reconstruction

3D from a single image and shape-from-x

Accurate 3D Face Reconstruction with Facial Component Tokens

HiFace: High-Fidelity 3D Face Reconstruction by Learning Static and Dynamic Details

Zero-1-to-3: Zero-shot One Image to 3D Object

Deformable Model-Driven Neural Rendering for High-Fidelity 3D Reconstruction of Human Heads Under Low-View Settings

3D Editing

Vox-E: Text-Guided Voxel Editing of 3D Objects

FaceCLIPNeRF: Text-driven 3D Face Manipulation using Deformable Neural Radiance Fields

SKED: Sketch-guided Text-based 3D Editing

Seal-3D: Interactive Pixel-Level Editing for Neural Radiance Fields

Face and gestures

Speech4Mesh: Speech-Assisted Monocular 3D Facial Reconstruction for Speech-Driven 3D Facial Animation

Imitator: Personalized Speech-driven 3D Facial Animation

EmoTalk: Speech-Driven Emotional Disentanglement for 3D Face Animation

SPACE: Speech-driven Portrait Animation with Controllable Expression

Stylization

Diffusion in Style

Creative Birds: Self-Supervised Single-View 3D Style Transfer

StyleDomain: Efficient and Lightweight Parameterizations of StyleGAN for One-shot and Few-shot Domain Adaptation

StylerDALLE: Language-Guided Style Transfer Using a Vector-Quantized Tokenizer of a Large-Scale Generative Model

X-Mesh: Towards Fast and Accurate Text-driven 3D Stylization via Dynamic Textual Guidance

Locally Stylized Neural Radiance Fields

DS-Fusion: Artistic Typography via Discriminated and Stylized Diffusion

Multi-Directional Subspace Editing in Style-Space

StyleDiffusion: Controllable Disentangled Style Transfer via Diffusion Models

All-to-Key Attention for Arbitrary Style Transfer

DeformToon3D: Deformable Neural Radiance Fields for 3D Toonification

Anti-DreamBooth: Protecting Users from Personalized Text-to-image Synthesis

Neural Collage Transfer: Artistic Reconstruction via Material Manipulation

Dataset

H3WB: Human3.6M 3D WholeBody Dataset and Benchmark

SynBody: Synthetic Dataset with Layered Human Models for 3D Human Perception and Modeling

Human-centric Scene Understanding for 3D Large-scale Scenario

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