no code implementations • CVPR 2023 • Haoming Lu, Hazarapet Tunanyan, Kai Wang, Shant Navasardyan, Zhangyang Wang, Humphrey Shi
Diffusion models have demonstrated impressive capability of text-conditioned image synthesis, and broader application horizons are emerging by personalizing those pretrained diffusion models toward generating some specialized target object or style.
no code implementations • 29 Sep 2021 • Minjie Wang, Haoming Lu, Yu Gai, Lesheng Jin, Zihao Ye, Zheng Zhang
Despite substantial efforts from the deep learning system community to relieve researchers and practitioners from the burden of implementing models with ever-growing complexity, a considerable lingual gap remains between developing models in the language of mathematics and implementing them in the languages of computer.
1 code implementation • 18 Sep 2020 • Haoming Lu, Humphrey Shi
The development of practical applications, such as autonomous driving and robotics, has brought increasing attention to 3D point cloud understanding.
2 code implementations • 20 Sep 2019 • Xiaofan Zhang, Haoming Lu, Cong Hao, Jiachen Li, Bowen Cheng, Yuhong Li, Kyle Rupnow, JinJun Xiong, Thomas Huang, Honghui Shi, Wen-mei Hwu, Deming Chen
Object detection and tracking are challenging tasks for resource-constrained embedded systems.
1 code implementation • 25 Jun 2019 • Xiaofan Zhang, Cong Hao, Haoming Lu, Jiachen Li, Yuhong Li, Yuchen Fan, Kyle Rupnow, JinJun Xiong, Thomas Huang, Honghui Shi, Wen-mei Hwu, Deming Chen
Developing artificial intelligence (AI) at the edge is always challenging, since edge devices have limited computation capability and memory resources but need to meet demanding requirements, such as real-time processing, high throughput performance, and high inference accuracy.