568 citations · 874 across the 25 of their papers we have counts for
26 papers
Structure First Detail Next: Image Inpainting with Pyramid Generator
Shuyi Qu, Zhenxing Niu, Kaizhu Huang +4
Recent deep generative models have achieved promising performance in image inpainting. However, it is still very challenging for a neural network to generate realistic image detail…
Accelerating Gossip SGD with Periodic Global Averaging
Yiming Chen, Kun Yuan, Yingya Zhang +3
Communication overhead hinders the scalability of large-scale distributed training. Gossip SGD, where each node averages only with its neighbors, is more communication-efficient th…
DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training
Kun Yuan, Yiming Chen, Xinmeng Huang +4
The scale of deep learning nowadays calls for efficient distributed training algorithms. Decentralized momentum SGD (DmSGD), in which each node averages only with its neighbors, is…
Learning Position and Target Consistency for Memory-based Video Object Segmentation
Li Hu, Peng Zhang, Bang Zhang +3
This paper studies the problem of semi-supervised video object segmentation(VOS). Multiple works have shown that memory-based approaches can be effective for video object segmentat…
Multiple Object Tracking with Correlation Learning
Qiang Wang, Yun Zheng, Pan Pan +1
Recent works have shown that convolutional networks have substantially improved the performance of multiple object tracking by simultaneously learning detection and appearance feat…
Few-Shot Incremental Learning with Continually Evolved Classifiers
Chi Zhang, Nan Song, Guosheng Lin +3
Few-shot class-incremental learning (FSCIL) aims to design machine learning algorithms that can continually learn new concepts from a few data points, without forgetting knowledge…
Self-supervised Video Representation Learning by Context and Motion Decoupling
Lianghua Huang, Yu Liu, Bin Wang +3
A key challenge in self-supervised video representation learning is how to effectively capture motion information besides context bias. While most existing works implicitly achieve…
Practical Relative Order Attack in Deep Ranking
Mo Zhou, Le Wang, Zhenxing Niu +4
Recent studies unveil the vulnerabilities of deep ranking models, where an imperceptible perturbation can trigger dramatic changes in the ranking result. While previous attempts fo…
Large-Scale Training System for 100-Million Classification at Alibaba
Liuyihan Song, Pan Pan, Kang Zhao +5
In the last decades, extreme classification has become an essential topic for deep learning. It has achieved great success in many areas, especially in computer vision and natural…
Train a One-Million-Way Instance Classifier for Unsupervised Visual Representation Learning
Yu Liu, Lianghua Huang, Pan Pan +3
This paper presents a simple unsupervised visual representation learning method with a pretext task of discriminating all images in a dataset using a parametric, instance-level cla…
Distribution Adaptive INT8 Quantization for Training CNNs
Kang Zhao, Sida Huang, Pan Pan +4
Researches have demonstrated that low bit-width (e.g., INT8) quantization can be employed to accelerate the inference process. It makes the gradient quantization very promising sin…
Fashion Focus: Multi-modal Retrieval System for Video Commodity Localization in E-commerce
Yanhao Zhang, Qiang Wang, Pan Pan +4
Nowadays, live-stream and short video shopping in E-commerce have grown exponentially. However, the sellers are required to manually match images of the selling products to the tim…
Virtual ID Discovery from E-commerce Media at Alibaba: Exploiting Richness of User Click Behavior for Visual Search Relevance
Yanhao Zhang, Pan Pan, Yun Zheng +4
Visual search plays an essential role for E-commerce. To meet the search demands of users and promote shopping experience at Alibaba, visual search relevance of real-shot images is…
Large-Scale Visual Search with Binary Distributed Graph at Alibaba
Kang Zhao, Pan Pan, Yun Zheng +5
Graph-based approximate nearest neighbor search has attracted more and more attentions due to its online search advantages. Numbers of methods studying the enhancement of speed and…
Large Scale Long-tailed Product Recognition System at Alibaba
Xiangzeng Zhou, Pan Pan, Yun Zheng +2
A practical large scale product recognition system suffers from the phenomenon of long-tailed imbalanced training data under the E-commercial circumstance at Alibaba. Besides produ…
Exploiting Diverse Characteristics and Adversarial Ambivalence for Domain Adaptive Segmentation
Bowen Cai, Huan Fu, Rongfei Jia +3
Adapting semantic segmentation models to new domains is an important but challenging problem. Recently enlightening progress has been made, but the performance of existing methods…
Weakly Supervised Learning with Side Information for Noisy Labeled Images
Lele Cheng, Xiangzeng Zhou, Liming Zhao +5
In many real-world datasets, like WebVision, the performance of DNN based classifier is often limited by the noisy labeled data. To tackle this problem, some image related side inf…
Balanced Order Batching with Task-Oriented Graph Clustering
Lu Duan, Haoyuan Hu, Zili Wu +4
Balanced order batching problem (BOBP) arises from the process of warehouse picking in Cainiao, the largest logistics platform in China. Batching orders together in the picking pro…
Accelerating Primal Solution Findings for Mixed Integer Programs Based on Solution Prediction
Jian-Ya Ding, Chao Zhang, Lei Shen +4
Mixed Integer Programming (MIP) is one of the most widely used modeling techniques for combinatorial optimization problems. In many applications, a similar MIP model is solved on a…
Can Sophisticated Dispatching Strategy Acquired by Reinforcement Learning? - A Case Study in Dynamic Courier Dispatching System
Yujie Chen, Yu Qian, Yichen Yao +5
In this paper, we study a courier dispatching problem (CDP) raised from an online pickup-service platform of Alibaba. The CDP aims to assign a set of couriers to serve pickup reque…
A Novel Bin Design Problem and High Performance Algorithm for E-commerce Logistics System
Xinhang Zhang, Haoyuan Hu, Longfei Wang +4
Packing cost accounts for a large part of the e-commerce logistics cost. Mining the patterns of customer orders and designing suitable packing bins help to reduce operating cost. I…
GP-CNAS: Convolutional Neural Network Architecture Search with Genetic Programming
Yiheng Zhu, Yichen Yao, Zili Wu +4
Convolutional neural networks (CNNs) are effective at solving difficult problems like visual recognition, speech recognition and natural language processing. However, performance g…
A Multi-task Selected Learning Approach for Solving 3D Flexible Bin Packing Problem
Lu Duan, Haoyuan Hu, Yu Qian +4
A 3D flexible bin packing problem (3D-FBPP) arises from the process of warehouse packing in e-commerce. An online customer's order usually contains several items and needs to be pa…
Reinforcement Learning to Rank in E-Commerce Search Engine: Formalization, Analysis, and Application
Yujing Hu, Qing Da, Anxiang Zeng +2
In e-commerce platforms such as Amazon and TaoBao, ranking items in a search session is a typical multi-step decision-making problem. Learning to rank (LTR) methods have been widel…