no code implementations • 5 May 2024 • Zhenyu Lou, Qiongjie Cui, Haofan Wang, Xu Tang, Hong Zhou
Predicting future human pose is a fundamental application for machine intelligence, which drives robots to plan their behavior and paths ahead of time to seamlessly accomplish human-robot collaboration in real-world 3D scenarios.
1 code implementation • 25 Feb 2024 • Luoming Zhang, Yefei He, Wen Fei, Zhenyu Lou, Weijia Wu, YangWei Ying, Hong Zhou
Our framework outperforms previous methods by approximately 1\% for 8-bit PTQ and 2\% for 6-bit PTQ, showcasing its superior performance.
no code implementations • 7 Oct 2023 • Luoming Zhang, Wen Fei, Weijia Wu, Yefei He, Zhenyu Lou, Hong Zhou
Fine-grained quantization has smaller quantization loss, consequently achieving superior performance.
no code implementations • ICCV 2023 • Yefei He, Zhenyu Lou, Luoming Zhang, Jing Liu, Weijia Wu, Hong Zhou, Bohan Zhuang
To solve this, we propose Softmax-aware Binarization, which dynamically adapts to the data distribution and reduces the error caused by binarization.
no code implementations • 14 Nov 2022 • Yefei He, Zhenyu Lou, Luoming Zhang, Jing Liu, Weijia Wu, Hong Zhou, Bohan Zhuang
To solve this, we propose Softmax-aware Binarization, which dynamically adapts to the data distribution and reduces the error caused by binarization.