Timing Yang

@carlosedubarret Thank you for your interest. Could you please share the configuration you used in run_demo.sh? Using different configurations might lead to varying FPS and accuracy.

Quick test done with Fast SAM 3d Body (BTW, it wasnt realtime fast on windows) took me 4 minutes to make this 6 seconds video.

@ChongZitaZhang Exactly! The original MHR conversion requires 300 iterations, which is a total bottleneck for real-time tasks. We replaced that process with a few MLP layers to strip away the latency while keeping the accuracy.

you know it is serious when the number is 10426x

@iam_shimon It is pity. They are different architectures, so we don’t prepare to work on SAM 3D objects.

@TimingYang99 Nicee! Do we have the same method working for SAM 3D objects? This can make the pick and place perception system much better.

🚀 Fast SAM 3D Body — accelerating SAM 3D Body for real-time human mesh recovery! ⚡ 10.25× faster 3D body estimation ⚡ 10,426× faster MHR→SMPL conversion ⏱️ ~65ms end-to-end 🤖 Deployable on humanoid robots #Robotics

@jackadoresai This depends on the capabilities of SAM 3D Body, which we have fully inherited. Additionally, we support multi-view input, which helps mitigate occlusion issues to a certain extent.

@TimingYang99 65ms end-to-end is wild. Real-time body estimation finally viable for humanoids. Curious how it handles heavy occlusion.

@jimezsa thank you

@TimingYang99 65ms is crazy

📄 arxiv.org/abs/2603.15603 🌐 yangtiming.github.io/Fast-SAM-3D-Bo… github.com/yangtiming/Fas…