Hongchi Xia

16 posts

Hongchi Xia

Hongchi Xia

@hongchix

Hi here is Hongchi Xia, a Ph.D. student in Computer Science at UIUC, My research lies in 3D computer vision. https://t.co/HBqneK3sGZ

Katılım Nisan 2025
43 Takip Edilen134 Takipçiler
Hongchi Xia
Hongchi Xia@hongchix·
To promote community research, we pre-generate 10k scenes with SAGE and name it the SAGE-10k dataset. The dataset contains 10,000 diverse scenes spanning 50 room types and styles, along with 565K uniquely generated 3D objects. Download link: huggingface.co/datasets/nvidi…
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Hongchi Xia
Hongchi Xia@hongchix·
Here we introduce SAGE: Scalable Agentic 3D Scene Generation for Embodied AI, which can generate sim-ready 3D scenes with agents following user demands at scale, ready for robotic action generation. Paper, code, and SAGE-10k dataset are all released! nvlabs.github.io/sage/
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Hongchi Xia
Hongchi Xia@hongchix·
I'll be at San Diego to present our #NeurIPS2025 paper! Please drop by on Friday, Dec. 5, from 4:30 to 7:30 pm at Exhibit Hall C,D,E #4901. Happy to share and discuss with everyone there!
Hongchi Xia@hongchix

#NeurIPS2025 We're excited to introduce <HoloScene>, which can create realistic and simulation-ready worlds from videos. It can recover every rigid-body object completeness, avoid geometry interpenetration, and maintain physical stability. Project page: xiahongchi.github.io/HoloScene/

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Hongchi Xia
Hongchi Xia@hongchix·
<HoloScene> is a joint project by me (Hongchi), Chih-Hao @ZhiHaoLin16, Hao-Yu (Max) @haoyuhsu88, Quentin, Katelyn, Michael, Benjamin, and Prof. Shenlong Wang @ShenlongWang Thanks for all your contributions!
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Hongchi Xia
Hongchi Xia@hongchix·
#NeurIPS2025 We're excited to introduce <HoloScene>, which can create realistic and simulation-ready worlds from videos. It can recover every rigid-body object completeness, avoid geometry interpenetration, and maintain physical stability. Project page: xiahongchi.github.io/HoloScene/
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Hongchi Xia
Hongchi Xia@hongchix·
Glad to introduce our #CVPR2025 paper "DRAWER", allowing one to create a realistic and interactable digital twin from a video of a static scene without any interactions with the environment. It unlocks many opportunities in gaming and robotics! Webpage: drawer-art.github.io
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