papers

Publications (27)

cs.CV2019

AMC: AutoML for Model Compression and Acceleration on Mobile Devices

Yihui He, Ji Lin, Zhijian Liu +3

Model compression is a critical technique to efficiently deploy neural network models on mobile devices which have limited computation resources and tight power budgets. Convention…

cs.CV2015

Multi-view Face Detection Using Deep Convolutional Neural Networks

Sachin Sudhakar Farfade, Mohammad Saberian, Li-Jia Li

In this paper we consider the problem of multi-view face detection. While there has been significant research on this problem, current state-of-the-art approaches for this task req…

eess.IV2023

USE-Evaluator: Performance Metrics for Medical Image Segmentation Models with Uncertain, Small or Empty Reference Annotations

Sophie Ostmeier, Brian Axelrod, Jeroen Bertels +6

Performance metrics for medical image segmentation models are used to measure the agreement between the reference annotation and the predicted segmentation. Usually, overlap metric…

cs.CV2018

Iterative Visual Reasoning Beyond Convolutions

Xinlei Chen, Li-Jia Li, Li Fei-Fei +1

We present a novel framework for iterative visual reasoning. Our framework goes beyond current recognition systems that lack the capability to reason beyond stack of convolutions.…

cs.CV2018

Composing Text and Image for Image Retrieval - An Empirical Odyssey

Nam Vo, Lu Jiang, Chen Sun +4

In this paper, we study the task of image retrieval, where the input query is specified in the form of an image plus some text that describes desired modifications to the input ima…

cs.CV2018

NOTE-RCNN: NOise Tolerant Ensemble RCNN for Semi-Supervised Object Detection

JIyang Gao, Jiang Wang, Shengyang Dai +2

The labeling cost of large number of bounding boxes is one of the main challenges for training modern object detectors. To reduce the dependence on expensive bounding box annotatio…