Search Results for author: Chengqian Ma

Found 6 papers, 1 papers with code

BigSmall: Efficient Multi-Task Learning for Disparate Spatial and Temporal Physiological Measurements

2 code implementations21 Mar 2023 Girish Narayanswamy, Yujia Liu, Yuzhe Yang, Chengqian Ma, Xin Liu, Daniel McDuff, Shwetak Patel

As an example, perception occurs at different scales both spatially and temporally, suggesting that the extraction of salient visual information may be made more effective by paying attention to specific features at varying scales.

Multi-Task Learning

IA-MOT: Instance-Aware Multi-Object Tracking with Motion Consistency

no code implementations24 Jun 2020 Jiarui Cai, Yizhou Wang, Haotian Zhang, Hung-Min Hsu, Chengqian Ma, Jenq-Neng Hwang

Meanwhile, the spatial attention, which focuses on the foreground within the bounding boxes, is generated from the given instance masks and applied to the extracted embedding features.

Multi-Object Tracking Multiple Object Tracking +1

Automated Backend-Aware Post-Training Quantization

no code implementations27 Mar 2021 Ziheng Jiang, Animesh Jain, Andrew Liu, Josh Fromm, Chengqian Ma, Tianqi Chen, Luis Ceze

Quantization is a key technique to reduce the resource requirement and improve the performance of neural network deployment.

Quantization

Rate-Perception Optimized Preprocessing for Video Coding

no code implementations25 Jan 2023 Chengqian Ma, Zhiqiang Wu, Chunlei Cai, Pengwei Zhang, Yi Wang, Long Zheng, Chao Chen, Quan Zhou

In the past decades, lots of progress have been done in the video compression field including traditional video codec and learning-based video codec.

Image Quality Assessment Video Compression

From Classification to Clinical Insights: Towards Analyzing and Reasoning About Mobile and Behavioral Health Data With Large Language Models

no code implementations21 Nov 2023 Zachary Englhardt, Chengqian Ma, Margaret E. Morris, Xuhai "Orson" Xu, Chun-Cheng Chang, Lianhui Qin, Daniel McDuff, Xin Liu, Shwetak Patel, Vikram Iyer

Passively collected behavioral health data from ubiquitous sensors holds significant promise to provide mental health professionals insights from patient's daily lives; however, developing analysis tools to use this data in clinical practice requires addressing challenges of generalization across devices and weak or ambiguous correlations between the measured signals and an individual's mental health.

Decision Making

Weather Prediction with Diffusion Guided by Realistic Forecast Processes

no code implementations6 Feb 2024 Zhanxiang Hua, Yutong He, Chengqian Ma, Alexandra Anderson-Frey

Weather forecasting remains a crucial yet challenging domain, where recently developed models based on deep learning (DL) have approached the performance of traditional numerical weather prediction (NWP) models.

Weather Forecasting

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