7 citations · 13 across the 27 of their papers we have counts for
28 papers · 1 filter
HarnessEval-W: Agentifying the Evaluation of Visual Worlds
Weiliang Chen, Haowen Sun, Jun Gao +40
A benchmark should deliver more than a scalar score: what makes an evaluation trustworthy is the reasoning that justifies the score. This is especially critical for world models, w…
Code as Worlds: Agentic Discovery of Executable World Representations for Physical Reasoning
Hanyang Wang, Yimo Cai, Weiliang Chen +14
Physical understanding and reasoning depend on forming compact and generalizable representations of the world. While modern vision-language models can recognize and explain diverse…
ToW3D: Consistency-aware Interactive Point-based Mesh Editing on GANs
Haixu Song, Fangfu Liu, Chenyu Zhang +1
In this paper, we propose ToW3D that enables precise and consistent control over 3D generative adversarial networks (GANs) with the Tug-of-War competition between shape deformation…
S-Agent: Spatial Tool-Use Elicits Reasoning for Spatial Intelligence
Yalun Dai, Hao Li, Shulin Tian +8
Real-world spatial intelligence requires reasoning over a continuous and evolving 3D world, yet existing VLMs and tool-augmented agents largely remain tied to static, stateless inf…
Gamma-World: Generative Multi-Agent World Modeling Beyond Two Players
Fangfu Liu, Kai He, Tianchang Shen +7
World models for interactive video generation have largely focused on single-agent settings, where future observations are generated from a single control signal. However, many gen…
GEM: Generative Supervision Helps Embodied Intelligence
Ruowen Zhao, Bangguo Li, Zuyan Liu +9
Embodied Vision-Language Models (VLMs) have demonstrated impressive performance and generalization in robotics, particularly within Vision-Language-Action frameworks. However, a si…
LoViF 2026 The First Challenge on Holistic Quality Assessment for 4D World Model (PhyScore)
Wei Luo, Yiting Lu, Xin Li +32
This paper reports on the LoViF 2026 PhyScore challenge, a competition on holistic quality assessment of world-model-generated videos across both 2D and 4D generation settings. The…
Spatial-TTT: Streaming Visual-based Spatial Intelligence with Test-Time Training
Fangfu Liu, Diankun Wu, Jiawei Chi +7
Humans perceive and understand real-world spaces through a stream of visual observations. Therefore, the ability to streamingly maintain and update spatial evidence from potentiall…
CFG-Ctrl: Control-Based Classifier-Free Diffusion Guidance
Hanyang Wang, Yiyang Liu, Jiawei Chi +3
Classifier-Free Guidance (CFG) has emerged as a central approach for enhancing semantic alignment in flow-based diffusion models. In this paper, we explore a unified framework call…
Holi-Spatial: Evolving Video Streams into Holistic 3D Spatial Intelligence
Yuanyuan Gao, Hao Li, Yifei Liu +14
The pursuit of spatial intelligence fundamentally relies on access to large-scale, fine-grained 3D data. However, existing approaches predominantly construct spatial understanding…
OnlineX: Unified Online 3D Reconstruction and Understanding with Active-to-Stable State Evolution
Chong Xia, Fangfu Liu, Yule Wang +2
Recent advances in generalizable 3D Gaussian Splatting (3DGS) have enabled rapid 3D scene reconstruction within seconds, eliminating the need for per-scene optimization. However, e…
SimRecon: SimReady Compositional Scene Reconstruction from Real Videos
Chong Xia, Kai Zhu, Zizhuo Wang +3
Compositional scene reconstruction seeks to create object-centric representations rather than holistic scenes from real-world videos, which is natively applicable for simulation an…
PanoWorld-X: Generating Explorable Panoramic Worlds via Sphere-Aware Video Diffusion
Yuyang Yin, HaoXiang Guo, Fangfu Liu +7
Generating a complete and explorable 360-degree visual world enables a wide range of downstream applications. While prior works have advanced the field, they remain constrained by…
ScenePainter: Semantically Consistent Perpetual 3D Scene Generation with Concept Relation Alignment
Chong Xia, Shengjun Zhang, Fangfu Liu +3
Perpetual 3D scene generation aims to produce long-range and coherent 3D view sequences, which is applicable for long-term video synthesis and 3D scene reconstruction. Existing met…
LangScene-X: Reconstruct Generalizable 3D Language-Embedded Scenes with TriMap Video Diffusion
Fangfu Liu, Hao Li, Jiawei Chi +4
Recovering 3D structures with open-vocabulary scene understanding from 2D images is a fundamental but daunting task. Recent developments have achieved this by performing per-scene…
Spatial-MLLM: Boosting MLLM Capabilities in Visual-based Spatial Intelligence
Diankun Wu, Fangfu Liu, Yi-Hsin Hung +1
Recent advancements in Multimodal Large Language Models (MLLMs) have significantly enhanced performance on 2D visual tasks. However, improving their spatial intelligence remains a…
VideoScene: Distilling Video Diffusion Model to Generate 3D Scenes in One Step
Hanyang Wang, Fangfu Liu, Jiawei Chi +1
Recovering 3D scenes from sparse views is a challenging task due to its inherent ill-posed problem. Conventional methods have developed specialized solutions (e.g., geometry regula…
Video-T1: Test-Time Scaling for Video Generation
Fangfu Liu, Hanyang Wang, Yimo Cai +3
With the scale capability of increasing training data, model size, and computational cost, video generation has achieved impressive results in digital creation, enabling users to e…
Gaussian Graph Network: Learning Efficient and Generalizable Gaussian Representations from Multi-view Images
Shengjun Zhang, Xin Fei, Fangfu Liu +2
3D Gaussian Splatting (3DGS) has demonstrated impressive novel view synthesis performance. While conventional methods require per-scene optimization, more recently several feed-for…
DimensionX: Create Any 3D and 4D Scenes from a Single Image with Controllable Video Diffusion
Wenqiang Sun, Shuo Chen, Fangfu Liu +4
In this paper, we introduce \textbf{DimensionX}, a framework designed to generate photorealistic 3D and 4D scenes from just a single image with video diffusion. Our approach begins…
ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model
Fangfu Liu, Wenqiang Sun, Hanyang Wang +5
Advancements in 3D scene reconstruction have transformed 2D images from the real world into 3D models, producing realistic 3D results from hundreds of input photos. Despite great s…
DreamCinema: Cinematic Transfer with Free Camera and 3D Character
Weiliang Chen, Fangfu Liu, Diankun Wu +3
We are living in a flourishing era of digital media, where everyone has the potential to become a personal filmmaker. Current research on video generation suggests a promising aven…
Physics3D: Learning Physical Properties of 3D Gaussians via Video Diffusion
Fangfu Liu, Hanyang Wang, Shunyu Yao +3
In recent years, there has been rapid development in 3D generation models, opening up new possibilities for applications such as simulating the dynamic movements of 3D objects and…
Unique3D: High-Quality and Efficient 3D Mesh Generation from a Single Image
Kailu Wu, Fangfu Liu, Zhihan Cai +5
In this work, we introduce Unique3D, a novel image-to-3D framework for efficiently generating high-quality 3D meshes from single-view images, featuring state-of-the-art generation…