activity
20142019
most citedDSSD : Deconvolutional Single Shot Detector

1.6k citations · 1.9k across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV20195 cited

Low-Power Computer Vision: Status, Challenges, Opportunities

Sergei Alyamkin, Matthew Ardi, Alexander C. Berg +41

Computer vision has achieved impressive progress in recent years. Meanwhile, mobile phones have become the primary computing platforms for millions of people. In addition to mobile…

cs.CV2019

Low Power Inference for On-Device Visual Recognition with a Quantization-Friendly Solution

Chen Feng, Tao Sheng, Zhiyu Liang +9

The IEEE Low-Power Image Recognition Challenge (LPIRC) is an annual competition started in 2015 that encourages joint hardware and software solutions for computer vision systems wi…

cs.CV2019119 cited

RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free

Cheng-Yang Fu, Mykhailo Shvets, Alexander C. Berg

Recently two-stage detectors have surged ahead of single-shot detectors in the accuracy-vs-speed trade-off. Nevertheless single-shot detectors are immensely popular in embedded vis…

cs.CV20171.6k cited

DSSD : Deconvolutional Single Shot Detector

Cheng-Yang Fu, Wei Liu, Ananth Ranga +2

The main contribution of this paper is an approach for introducing additional context into state-of-the-art general object detection. To achieve this we first combine a state-of-th…

cs.CV201654 cited

Modeling Context in Referring Expressions

Licheng Yu, Patrick Poirson, Shan Yang +2

Humans refer to objects in their environments all the time, especially in dialogue with other people. We explore generating and comprehending natural language referring expressions…

cs.CV201453 cited

ImageNet Large Scale Visual Recognition Challenge

Olga Russakovsky, Jia Deng, Hao Su +9

The ImageNet Large Scale Visual Recognition Challenge is a benchmark in object category classification and detection on hundreds of object categories and millions of images. The ch…