Update README.md

YandanYang · Jul 22, 2024 · 913534d · 913534d
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@@ -9,8 +9,7 @@ A curated list of awesome Indoor Scene Synthesis papers.
 
 ## Papers
 
-<details open>
-<summary>3D Scene synthesis</summary>
+### 3D Scene synthesis
 
 <details open>
 <summary>Compositional Mesh Generation</summary>
@@ -46,45 +45,70 @@ A curated list of awesome Indoor Scene Synthesis papers.
 - [Fast and Flexible Indoor Scene Synthesis via Deep Convolutional Generative Models](https://arxiv.org/abs/1811.12463) | CVPR 2019
 - [Scene Synthesis via Uncertainty-Driven Attribute Synchronization](https://arxiv.org/abs/2108.13499) | ICCV 2021 | [github](https://github.com/brownvc/fast-synth)
 - [RoomDesigner: Encoding Anchor-latents for Style-consistent and Shape-compatible Indoor Scene Generation](https://arxiv.org/abs/2310.10027), Zhao et al., 3DV 2024 | [github](https://github.com/zhao-yiqun/RoomDesigner) | [bibtext](./citations/roomdesigner.txt)
+</details>
 
-- 
-- Model training with scene graph
+<details open>
+<summary>Model Training with Scene Graph</summary>
+
 - [InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior](https://arxiv.org/abs/2402.04717) | ICLR 2024 | [github](https://github.com/chenguolin/InstructScene) | [project](https://chenguolin.github.io/projects/InstructScene/)
 - [CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graph Diffusion](https://arxiv.org/abs/2305.16283) | NIPS 2023 | [github](https://github.com/ymxlzgy/commonscenes) | [project](https://sites.google.com/view/commonscenes)
 - [3D Scene Diffusion Guidance using Scene Graphs](https://arxiv.org/abs/2308.04468) | arXiv 2023
 - [SceneGraphNet: Neural Message Passing for 3D Indoor Scene Augmentation](https://arxiv.org/abs/1907.11308) | ICCV 2019
+</details>
 
-
-- using 2D prior
+<details open>
+<summary>Using 2D Prior</summary>
+
 - [Lay-A-Scene: Personalized 3D Object Arrangement Using Text-to-Image Priors](https://arxiv.org/abs/2406.00687) | [project](https://lay-a-scene.github.io/)
+ </details>
 
+<details open>
+<summary>Procedure / Human Design Rules</summary>
 
-- procedure / human design rules
 - [Infinigen Indoors: Photorealistic Indoor Scenes using Procedural Generation](https://arxiv.org/abs/2406.11824)  | [github](https://github.com/princeton-vl/infinigen) | [project](https://infinigen.org/)
 - [Holodeck: Language Guided Generation of 3D Embodied AI Environments](https://arxiv.org/abs/2312.09067) | [github](https://github.com/allenai/Holodeck) | [project](https://yueyang1996.github.io/holodeck/)
 - [I-Design: Personalized LLM Interior Designer](https://arxiv.org/abs/2404.02838), arxiv 2024 | [github](https://github.com/atcelen/IDesign/?tab=readme-ov-file) | [project](https://atcelen.github.io/I-Design/)
 - [ProcTHOR: Large-Scale Embodied AI Using Procedural Generation](https://procthor.allenai.org/), Deitke et al., NeurIPS 2022 |  [github](https://github.com/allenai/procthor) | [bibtex](./citations/procthor.txt)
 </details>
 
-
-- MCMC
 
-- [Configurable 3D Scene Synthesis and 2D Image Rendering with Per-Pixel Ground Truth using Stochastic Grammars](https://arxiv.org/abs/1704.00112) | IJCV (2018)
+
+<details open>
+<summary>Conditioned on Human Montion</summary>
+
+- [Scene Synthesis from Human Motion](https://arxiv.org/abs/2301.01424) | SIGGRAPH Asia 2022 | [github](https://github.com/onestarYX/summon) | [project](https://lijiaman.github.io/projects/summon/)
+- [Pose2Room: Understanding 3D Scenes from Human Activities](https://arxiv.org/abs/2112.03030) | ECCV 2022 | [github](https://arxiv.org/abs/2112.03030) | [project](https://yinyunie.github.io/pose2room-page/)
+- [Human-centric Indoor Scene Synthesis Using Stochastic Grammar](https://arxiv.org/abs/1808.08473v1) | CVPR 2018
+- [Rearrange Indoor Scenes for Human-Robot Co-Activity](https://arxiv.org/abs/2303.05676) | ICRA 2023 | [github](https://github.com/Rayckey/scene_coactivity) | [project](https://sites.google.com/view/coactivity)
+- [MIME: Human-Aware 3D Scene Generation](https://arxiv.org/abs/2212.04360) | CVPR 2023 | [github](https://github.com/yhw-yhw/MIME) | [project](https://mime.is.tue.mpg.de/)
+- [Language-driven Scene Synthesis using Multi-conditional Diffusion Model](https://arxiv.org/abs/2310.15948) | arXiv 2023 | [github](https://github.com/andvg3/LSDM) | [project](https://lang-scene-synth.github.io/)
 </details>
 
+
 <details open>
-<summary>Scene Texture</summary>
+<summary>Condition on 2D Image</summary>
 
-- [Text2Scene: Text-driven Indoor Scene Stylization with Part-aware Details](https://arxiv.org/abs/2308.16880) | CVPR 2023
+- [Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes from a Single Image](https://arxiv.org/abs/2002.12212) | CVPR 2020 | [github](https://github.com/GAP-LAB-CUHK-SZ/Total3DUnderstanding) | [project](https://yinyunie.github.io/Total3D/)
+- [Holistic 3D Scene Understanding from a Single Image with Implicit Representation](https://arxiv.org/pdf/2103.06422) | CVPR 2021 | [github](https://github.com/chengzhag/Implicit3DUnderstanding) |[project](https://chengzhag.github.io/publication/im3d/)
 </details>
 
 
+
 <details open>
-<summary>2D Layout / General layout</summary>
+<summary>MCMC</summary>
 
-- [LayoutTransformer: Layout Generation and Completion with Self-attention](https://arxiv.org/abs/2006.14615) | ICCV2021 | [github](https://github.com/kampta/DeepLayout) | [project](https://kampta.github.io/layout/)
+- [Configurable 3D Scene Synthesis and 2D Image Rendering with Per-Pixel Ground Truth using Stochastic Grammars](https://arxiv.org/abs/1704.00112) | IJCV (2018)
 </details>
 
+### Scene Texture
+
+- [Text2Scene: Text-driven Indoor Scene Stylization with Part-aware Details](https://arxiv.org/abs/2308.16880) | CVPR 2023
+
+
+### 2D Layout / General layout
+
+- [LayoutTransformer: Layout Generation and Completion with Self-attention](https://arxiv.org/abs/2006.14615) | ICCV2021 | [github](https://github.com/kampta/DeepLayout) | [project](https://kampta.github.io/layout/)
+</details>
 
 <details open>
 <summary>Scene</summary>
@@ -102,26 +126,6 @@ A curated list of awesome Indoor Scene Synthesis papers.
 </details>
 
 
-<details open>
-<summary>conditioned on Human Montion</summary>
-
-- [Scene Synthesis from Human Motion](https://arxiv.org/abs/2301.01424) | SIGGRAPH Asia 2022 | [github](https://github.com/onestarYX/summon) | [project](https://lijiaman.github.io/projects/summon/)
-- [Pose2Room: Understanding 3D Scenes from Human Activities](https://arxiv.org/abs/2112.03030) | ECCV 2022 | [github](https://arxiv.org/abs/2112.03030) | [project](https://yinyunie.github.io/pose2room-page/)
-- [Human-centric Indoor Scene Synthesis Using Stochastic Grammar](https://arxiv.org/abs/1808.08473v1) | CVPR 2018
-- [Rearrange Indoor Scenes for Human-Robot Co-Activity](https://arxiv.org/abs/2303.05676) | ICRA 2023 | [github](https://github.com/Rayckey/scene_coactivity) | [project](https://sites.google.com/view/coactivity)
-- [MIME: Human-Aware 3D Scene Generation](https://arxiv.org/abs/2212.04360) | CVPR 2023 | [github](https://github.com/yhw-yhw/MIME) | [project](https://mime.is.tue.mpg.de/)
-- [Language-driven Scene Synthesis using Multi-conditional Diffusion Model](https://arxiv.org/abs/2310.15948) | arXiv 2023 | [github](https://github.com/andvg3/LSDM) | [project](https://lang-scene-synth.github.io/)
-</details>
-
-
-<details open>
-<summary>Condition on 2D Image</summary>
-
-- [Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes from a Single Image](https://arxiv.org/abs/2002.12212) | CVPR 2020 | [github](https://github.com/GAP-LAB-CUHK-SZ/Total3DUnderstanding) | [project](https://yinyunie.github.io/Total3D/)
-- [Holistic 3D Scene Understanding from a Single Image with Implicit Representation](https://arxiv.org/pdf/2103.06422) | CVPR 2021 | [github](https://github.com/chengzhag/Implicit3DUnderstanding) |[project](https://chengzhag.github.io/publication/im3d/)
-</details>
-
-
 
 
 ## Datasets