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20232026
most citedSweetDreamer: Aligning Geometric Priors in 2D Diffusion for Consistent Text-to-3D

19 citations · 26 across the 15 of their papers we have counts for

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cs.CV2026

ScenePlacer: Reformulating Scene-Level Object Pose Estimation as Visibility Field Learning

Ken Deng, Jiarui Liu, Guibiao Liao +7

We present ScenePlacer, a framework for scene-level pose estimation of objects generated by state-of-the-art native shape generation models, placing generated 3D objects into scene…

cs.CV2026

SPOON: Towards Coherent Compositional 3D Scene Generation from Uncalibrated Multi-view Images

Guibiao Liao, Mochu Xiang, Heng Li +6

Compositional 3D scene generation aims to recover complete 3D object shapes and their spatial arrangement from visual observations. Recent image-conditioned 3D generators provide s…

cs.CV2026

ReconPlusGen: Injecting Reconstruction Prior into Multi-view 3D Generation through Noise Inversion and Modulation

Jiarui Liu, Heng Li, Weiyu Li +7

Qualitative results and an illustration of our core idea. Top left: reconstruction results on benchmark images. Top right: reconstruction results on real-world images. Bottom: illu…

cs.CV2026

SpatialCrafter: Single Image World Modeling with Generative 3D Proxies

Chuan Fang, Lingteng Qiu, Yixun Liang +8

Explorable image-to-scene generation is essential for applications in gaming, robotics, and virtual reality. Existing methods based on video diffusion model (VDM) commonly rely on…

cs.CV2026

Rosetta: Composable Native Multimodal Pretraining

Xiangyue Liu, Zijian Zhang, Miles Yang +3

Achieving true artificial general intelligence requires foundation models capable of integrating new modalities without forgetting prior knowledge. However, accommodating continuou…

cs.CV2026

MeshFlow: Efficient Artistic Mesh Generation via MeshVAE and Flow-based Diffusion Transformer

Weiyu Li, Antoine Toisoul, Tom Monnier +4

We present MeshFlow, a new method for generating artist-like 3D meshes. Current mesh generators often adopt Auto-Regressive (AR) next-token prediction, a natural choice given the d…

cs.CV2026

AutoWeather4D: Autonomous Driving Video Weather Conversion via G-Buffer Dual-Pass Editing

Tianyu Liu, Weitao Xiong, Kunming Luo +4

Generative video models have significantly advanced the photorealistic synthesis of adverse weather for autonomous driving; however, they consistently demand massive datasets to le…

cs.CV2026

Symbiotic-MoE: Unlocking the Synergy between Generation and Understanding

Xiangyue Liu, Zijian Zhang, Miles Yang +3

Empowering Large Multimodal Models (LMMs) with image generation often leads to catastrophic forgetting in understanding tasks due to severe gradient conflicts. While existing parad…

cs.CV2025

SceneMaker: Open-set 3D Scene Generation with Decoupled De-occlusion and Pose Estimation Model

Yukai Shi, Weiyu Li, Zihao Wang +4

We propose a decoupled 3D scene generation framework called SceneMaker in this work. Due to the lack of sufficient open-set de-occlusion and pose estimation priors, existing method…

cs.CV2025

PoseMaster: A Unified 3D Native Framework for Stylized Pose Generation

Hongyu Yan, Kunming Luo, Weiyu Li +5

Pose stylization, which aims to synthesize stylized content aligning with target poses, serves as a fundamental task across 2D, 3D, and video domains. In the 3D realm, prevailing a…

cs.CV2025★ 1 cited

UniTEX: Universal High Fidelity Generative Texturing for 3D Shapes

Yixun Liang, Kunming Luo, Xiao Chen +5

We present UniTEX, a novel two-stage 3D texture generation framework to create high-quality, consistent textures for 3D assets. Existing approaches predominantly rely on UV-based i…

cs.CV2025★ 1 cited

Step1X-3D: Towards High-Fidelity and Controllable Generation of Textured 3D Assets

Weiyu Li, Xuanyang Zhang, Zheng Sun +15

While generative artificial intelligence has advanced significantly across text, image, audio, and video domains, 3D generation remains comparatively underdeveloped due to fundamen…

cs.CV2024

Dora: Sampling and Benchmarking for 3D Shape Variational Auto-Encoders

Rui Chen, Jianfeng Zhang, Yixun Liang +7

Recent 3D content generation pipelines commonly employ Variational Autoencoders (VAEs) to encode shapes into compact latent representations for diffusion-based generation. However,…

cs.CV2024

GeoWizard: Unleashing the Diffusion Priors for 3D Geometry Estimation from a Single Image

Xiao Fu, Wei Yin, Mu Hu +6

We introduce GeoWizard, a new generative foundation model designed for estimating geometric attributes, e.g., depth and normals, from single images. While significant research has…

cs.CV2023★ 19 cited

SweetDreamer: Aligning Geometric Priors in 2D Diffusion for Consistent Text-to-3D

Weiyu Li, Rui Chen, Xuelin Chen +1

It is inherently ambiguous to lift 2D results from pre-trained diffusion models to a 3D world for text-to-3D generation. 2D diffusion models solely learn view-agnostic priors and t…