Jixuan He — accepted AI-conference papers

2025

Restage4D: Reanimating Deformable 3D Reconstruction from a Single Video

Jixuan He, Chieh Hubert Lin, Lu Qi, Ming-Hsuan Yang

NeurIPS 2025poster

Motion is one of the key components in deformable 3D scenes. Generative video models allow users to animate static scenes with text prompts for novel motion, but when it comes to 4D reconstruction, such reanimations often fall apart. The generated videos often suffer from geometric artifacts, implau…

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2024

R^2-Tuning: Efficient Image-to-Video Transfer Learning for Video Temporal Grounding

Ye Liu, Jixuan He, Wanhua Li*, Junsik Kim, Donglai Wei, Hanspeter Pfister +1

ECCV 2024poster

"Video temporal grounding (VTG) is a fine-grained video understanding problem that aims to ground relevant clips in untrimmed videos given natural language queries. Most existing VTG models are built upon frame-wise final-layer CLIP features, aided by additional temporal backbones (, SlowFast) with…

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