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20242026
most citedFrom an Image to a Scene: Learning to Imagine the World from a Million 360 Videos

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cs.CV2026

FIRE3D: Feed-forward Interactive 3D Scene Reconstruction Within A Minute

Hongchi Xia, Tianhang Cheng, Wei-Chiu Ma +1

We present FIRE3D, a unified framework that takes a single RGB image or casual RGB video and transforms it into simulation-ready 3D scene assets for games and interactive applicati…

cs.CV2026

Thinking in Blender: Staged Executable Inverse Graphics with Vision-Language Models

Guangzhao He, Rundong Luo, Wei-Chiu Ma +1

Inverse graphics is a longstanding and highly underconstrained problem that seeks to reconstruct images as editable 3D scenes which can be rendered, relit, and manipulated. In this…

cs.CV2026

Seeing Fast and Slow: Learning the Flow of Time in Videos

Yen-Siang Wu, Rundong Luo, Jingsen Zhu +6

How can we tell whether a video has been sped up or slowed down? How can we generate videos at different speeds? Although videos have been central to modern computer vision researc…

cs.CV2026

SAGE: Scalable Agentic 3D Scene Generation for Embodied AI

Hongchi Xia, Xuan Li, Zhaoshuo Li +9

Real-world data collection for embodied agents remains costly and unsafe, calling for scalable, realistic, and simulator-ready 3D environments. However, existing scene-generation s…

cs.CV2025

Eval3D: Interpretable and Fine-grained Evaluation for 3D Generation

Shivam Duggal, Yushi Hu, Oscar Michel +7

Despite the unprecedented progress in the field of 3D generation, current systems still often fail to produce high-quality 3D assets that are visually appealing and geometrically a…

cs.CV2025

DRAWER: Digital Reconstruction and Articulation With Environment Realism

Hongchi Xia, Entong Su, Marius Memmel +7

Creating virtual digital replicas from real-world data unlocks significant potential across domains like gaming and robotics. In this paper, we present DRAWER, a novel framework th…