activity
20152023
most citedTraining Deeper Convolutional Networks with Deep Supervision

167 citations · 211 across the 8 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

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

A Simple Semi-Supervised Learning Framework for Object Detection

Kihyuk Sohn, Zizhao Zhang, Chun-Liang Li +3

Semi-supervised learning (SSL) has a potential to improve the predictive performance of machine learning models using unlabeled data. Although there has been remarkable recent prog…

cs.CV2019

Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation

Chen-Yu Lee, Tanmay Batra, Mohammad Haris Baig +1

In this work, we connect two distinct concepts for unsupervised domain adaptation: feature distribution alignment between domains by utilizing the task-specific decision boundary a…

cs.CV2016

Recursive Recurrent Nets with Attention Modeling for OCR in the Wild

Chen-Yu Lee, Simon Osindero

We present recursive recurrent neural networks with attention modeling (RAM) for lexicon-free optical character recognition in natural scene images. The primary advantages of t…

cs.CV2015167 cited

Training Deeper Convolutional Networks with Deep Supervision

Liwei Wang, Chen-Yu Lee, Zhuowen Tu +1

One of the most promising ways of improving the performance of deep convolutional neural networks is by increasing the number of convolutional layers. However, adding layers makes…