activity
20152020
most citedBag of Freebies for Training Object Detection Neural Networks

147 citations · 245 across the 7 of their papers we have counts for

collaborators

17 papers

cs.CV20201 cited

Differential Viewpoints for Ground Terrain Material Recognition

Jia Xue, Hang Zhang, Ko Nishino +1

Computational surface modeling that underlies material recognition has transitioned from reflectance modeling using in-lab controlled radiometric measurements to image-based repres…

cs.CV202012 cited

Character Matters: Video Story Understanding with Character-Aware Relations

Shijie Geng, Ji Zhang, Zuohui Fu +3

Different from short videos and GIFs, video stories contain clear plots and lists of principal characters. Without identifying the connection between appearing people and character…

cs.CV202035 cited

Improving Semantic Segmentation via Self-Training

Yi Zhu, Zhongyue Zhang, Chongruo Wu +6

Deep learning usually achieves the best results with complete supervision. In the case of semantic segmentation, this means that large amounts of pixelwise annotations are required…

cs.CV2020

ResNeSt: Split-Attention Networks

Hang Zhang, Chongruo Wu, Zhongyue Zhang +9

It is well known that featuremap attention and multi-path representation are important for visual recognition. In this paper, we present a modularized architecture, which applies t…

stat.ML2020

AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data

Nick Erickson, Jonas Mueller, Alexander Shirkov +4

We introduce AutoGluon-Tabular, an open-source AutoML framework that requires only a single line of Python to train highly accurate machine learning models on an unprocessed tabula…

stat.ML201932 cited

Small-GAN: Speeding Up GAN Training Using Core-sets

Samarth Sinha, Han Zhang, Anirudh Goyal +3

Recent work by Brock et al. (2018) suggests that Generative Adversarial Networks (GANs) benefit disproportionately from large mini-batch sizes. Unfortunately, using large batches i…