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[IJCV 2021] SportsCap: Monocular 3D Human Motion Capture and Fine-grained Understanding in Challenging Sports Videos

Jupyter Notebook 46.41% Python 53.59%

sportscap's Introduction

Hi there, I am Chris (Chen Xin, 陈欣).

👨🏼‍💻 I’m a Research Scientist at Tencent, Shanghai.
🔭 I’m currently working on Generative AI and Multimodal Models, including Language Driven Model and 3D AIGC.
📖 Recent works: Motion-Latent-Diffusion and MotionGPT, a unified and user-friendly motion-language model using LLMs.
📖 Recent works: Paint3D, a lighting-less texture diffusion model.
📖 Recent works: AppAgent, a multimodal agent for smartphone apps.
📖 Recent works: LL3DA and M3DBench , a multimodal-language 3D assistant and benchmark.

MotionGPT	Paint3D	AppAgent
teaser_video.mp4	paint3d_vid_720p.mp4	AppAgent_demo.mp4

trendingtechnology stevenjokess xujinglin goyallon marisssssa yahyaghani easy-shu peterzs knight-mao sshuster ramonfigueiredo

If you see it, can you private message me and I would like to get in touch with you for some help. Thank you very much.

Hi,

Thank you for your work! I was hoping to use the complete dataset and was wondering if you can provide access to the remaining action categories.

Are there paired images for the marker-based mocap data?

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