[ICCV-23] Paper List - 3D Generation-related

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

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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

• Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields (pdf)：Instant-NGP提出grid-based NeRF，对NeRF提速。Grid-based NeRF通常存在锯齿问题（alias），因此mip-NeRF 360提出将采样由射线变为圆锥，实现抗锯齿（Anti-aliasing）。但是，mip-NeRF 360不能很好的与Instant-NGP结合，因此本文提出了zip-NeRF。
• LERF: Language Embedded Radiance Fields (pdf) ：LERF是DFF的后续工作，在DINO features的基础上，额外引入了CLIP features，帮助实现NeRF中的细粒度定位和分类。

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