activity
20172021
most citedSkeleton-Based Action Recognition with Multi-Stream Adaptive Graph Convolutional Networks

547 citations · 1.2k across the 24 of their papers we have counts for

collaborators

24 papers

cs.CL2021★ 13 cited

QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction

Danqing Zhang, Zheng Li, Tianyu Cao +7

We study the problem of query attribute value extraction, which aims to identify named entities from user queries as diverse surface form attribute values and afterward transform t…

cs.CV2021★ 21 cited

OPT: Omni-Perception Pre-Trainer for Cross-Modal Understanding and Generation

Jing Liu, Xinxin Zhu, Fei Liu +8

In this paper, we propose an Omni-perception Pre-Trainer (OPT) for cross-modal understanding and generation, by jointly modeling visual, text and audio resources. OPT is constructe…

cs.CL2021

Graph-based Multilingual Product Retrieval in E-commerce Search

Hanqing Lu, Youna Hu, Tong Zhao +3

Nowadays, with many e-commerce platforms conducting global business, e-commerce search systems are required to handle product retrieval under multilingual scenarios. Moreover, comp…

cs.CV2021

AdaSGN: Adapting Joint Number and Model Size for Efficient Skeleton-Based Action Recognition

Lei Shi, Yifan Zhang, Jian Cheng +1

Existing methods for skeleton-based action recognition mainly focus on improving the recognition accuracy, whereas the efficiency of the model is rarely considered. Recently, there…

cs.CL2021★ 7 cited

Fast Sequence Generation with Multi-Agent Reinforcement Learning

Longteng Guo, Jing Liu, Xinxin Zhu +1

Autoregressive sequence Generation models have achieved state-of-the-art performance in areas like machine translation and image captioning. These models are autoregressive in that…

cs.CV2020★ 27 cited

Decoupled Spatial-Temporal Attention Network for Skeleton-Based Action Recognition

Lei Shi, Yifan Zhang, Jian Cheng +1

Dynamic skeletal data, represented as the 2D/3D coordinates of human joints, has been widely studied for human action recognition due to its high-level semantic information and env…