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DR. DONG HUANG

I work on Dense Supervision approaches for efficient deep learning perception:


1. Perception on embedded platforms: My research team at RI CMU empowers cameras and sensors on moving platforms-autonomous machines, drones, smart camera modules-with (a) the light-weight Deep Neural Networks (DNNs) that consume less computation, memory, and power than standard deep learning approaches, and (b) the advanced training approaches that improve performance on embedded platforms without overheads on deployment efforts, training data and testing computation. We are making intelligent perception solutions accessible for general industries and markets.


2. Perception in multi-modality systems: We develop deep learning approaches that take multiple sensor data (e.g., videos, depth, wearable sensor signal, and WiFi signal) to produce multiple perception results, such as location, poses, activities, and physical metrics. Our deep approaches also trace the key factors of perception results for the purpose of improving the psychical performance of athletes and quality-of-life for the general public.

Office:

5000 Forbes Ave., EDSH 111, Pittsburgh, PA 15213

Affiliation:

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Sponsors/Partners:

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HIRING 2022

New Positions are available for Postdocs, Research Engineers, and graduate-level Research Associates! Please email me about your interests and experiences.  

RESEARCH GALLERY

Portable Person Detector on Nvidia Jetson TX2

Portable Person Detector on Nvidia Jetson TX2
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Portable Person Detector on Nvidia Jetson TX2
00:54
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Portable Person Detector on Nvidia Jetson TX2

Person in WiFi: See body shapes and poses using WiFi antennas
01:33
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Person in WiFi: See body shapes and poses using WiFi antennas

Detecting Body Poses for Construction Safeguarding
01:11
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Detecting Body Poses for Construction Safeguarding

EVENTS

Aug.2021: Tech news on our WiFi sensing technology on Post-Gazette News Link
Jul. 2021: Elaborative Rehearsal for Zero-shot Action Recognition accepted by ICCV 2021!
Mar. 2021: Optimal Gradient Checkpoint Search for Arbitrary Computation Graphs accepted by CVPR 2021 (Oral)! 

Sep. 2020: Comprehensive Attention Self-Distillation (CASD) accepted by NeurIPS 2020!
Aug. 2020: RSC and MAL codes released in our [Github]
Jun. 2020: Representation Self-Challenging (RSC) accepted by ECCV 2020 Oral (top 2%)! 
Feb. 2020: Multiple Anchor Learning (MAL) accepted by CVPR 2020! 
Sep. 2019: Inverted Attention (IA) accepted by WACV 2020! 
Jul. 2019: Person-in-WiFi accepted by ICCV 2019! 
May. 2019: 9 Papers on Deep Learning Research 
Mar. 2019: DeLight Group at Robotics Institute, CMU