activity
20202022
most citedTowards Transmission-Friendly and Robust CNN Models over Cloud and Device

28 citations · 69 across the 7 of their papers we have counts for

collaborators

8 papers

cs.DC2022★ 28 cited

Towards Transmission-Friendly and Robust CNN Models over Cloud and Device

Chuntao Ding, Zhichao Lu, Felix Juefei-Xu +3

Deploying deep convolutional neural network (CNN) models on ubiquitous Internet of Things (IoT) devices has attracted much attention from industry and academia since it greatly fac…

cs.CV2022★ 12 cited

VLMixer: Unpaired Vision-Language Pre-training via Cross-Modal CutMix

Teng Wang, Wenhao Jiang, Zhichao Lu +4

Existing vision-language pre-training (VLP) methods primarily rely on paired image-text datasets, which are either annotated by enormous human labors, or crawled from the internet…

cs.CV2022★ 2 cited

Semantic-Aware Pretraining for Dense Video Captioning

Teng Wang, Zhu Liu, Feng Zheng +3

This report describes the details of our approach for the event dense-captioning task in ActivityNet Challenge 2021. We present a semantic-aware pretraining method for dense video…

cs.CV2022★ 3 cited

GAMMA Challenge:Glaucoma grAding from Multi-Modality imAges

Junde Wu, Huihui Fang, Fei Li +26

Color fundus photography and Optical Coherence Tomography (OCT) are the two most cost-effective tools for glaucoma screening. Both two modalities of images have prominent biomarker…

cs.CV2021

Learning from Weakly-labeled Web Videos via Exploring Sub-Concepts

Kunpeng Li, Zizhao Zhang, Guanhang Wu +5

Learning visual knowledge from massive weakly-labeled web videos has attracted growing research interests thanks to the large corpus of easily accessible video data on the Internet…

cs.CV2020★ 9 cited

PERF-Net: Pose Empowered RGB-Flow Net

Yinxiao Li, Zhichao Lu, Xuehan Xiong +1

In recent years, many works in the video action recognition literature have shown that two stream models (combining spatial and temporal input streams) are necessary for achieving…

cs.CV2020

DOPS: Learning to Detect 3D Objects and Predict their 3D Shapes

Mahyar Najibi, Guangda Lai, Abhijit Kundu +7

We propose DOPS, a fast single-stage 3D object detection method for LIDAR data. Previous methods often make domain-specific design decisions, for example projecting points into a b…

cs.CV2020★ 15 cited

RetinaTrack: Online Single Stage Joint Detection and Tracking

Zhichao Lu, Vivek Rathod, Ronny Votel +1

Traditionally multi-object tracking and object detection are performed using separate systems with most prior works focusing exclusively on one of these aspects over the other. Tra…