52 citations · 271 across the 17 of their papers we have counts for
17 papers
Decoupled Mixup for Generalized Visual Recognition
Haozhe Liu, Wentian Zhang, Jinheng Xie +7
Convolutional neural networks (CNN) have demonstrated remarkable performance when the training and testing data are from the same distribution. However, such trained CNN models oft…
PIC 4th Challenge: Semantic-Assisted Multi-Feature Encoding and Multi-Head Decoding for Dense Video Captioning
Yifan Lu, Ziqi Zhang, Yuxin Chen +3
The task of Dense Video Captioning (DVC) aims to generate captions with timestamps for multiple events in one video. Semantic information plays an important role for both localizat…
CREATE: A Benchmark for Chinese Short Video Retrieval and Title Generation
Ziqi Zhang, Yuxin Chen, Zongyang Ma +5
Previous works of video captioning aim to objectively describe the video's actual content, which lacks subjective and attractive expression, limiting its practical application scen…
DistFL: Distribution-aware Federated Learning for Mobile Scenarios
Bingyan Liu, Yifeng Cai, Ziqi Zhang +5
Federated learning (FL) has emerged as an effective solution to decentralized and privacy-preserving machine learning for mobile clients. While traditional FL has demonstrated its…
Alleviating Noisy-label Effects in Image Classification via Probability Transition Matrix
Ziqi Zhang, Yuexiang Li, Hongxin Wei +3
Deep-learning-based image classification frameworks often suffer from the noisy label problem caused by the inter-observer variation. Recent studies employed learning-to-learn para…
Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition
Yuxin Chen, Ziqi Zhang, Chunfeng Yuan +3
Graph convolutional networks (GCNs) have been widely used and achieved remarkable results in skeleton-based action recognition. In GCNs, graph topology dominates feature aggregatio…
ModelDiff: Testing-Based DNN Similarity Comparison for Model Reuse Detection
Yuanchun Li, Ziqi Zhang, Bingyan Liu +2
The knowledge of a deep learning model may be transferred to a student model, leading to intellectual property infringement or vulnerability propagation. Detecting such knowledge r…
PDNet: Toward Better One-Stage Object Detection With Prediction Decoupling
Li Yang, Yan Xu, Shaoru Wang +4
Recent one-stage object detectors follow a per-pixel prediction approach that predicts both the object category scores and boundary positions from every single grid location. Howev…
Open-book Video Captioning with Retrieve-Copy-Generate Network
Ziqi Zhang, Zhongang Qi, Chunfeng Yuan +4
Due to the rapid emergence of short videos and the requirement for content understanding and creation, the video captioning task has received increasing attention in recent years.…
Depth Self-Optimized Learning Toward Data Science
Ziqi Zhang
We propose a two-stage model called Depth Self-Optimized Learning (DSOL), which aims to realize ANN depth self-configuration, self-optimization as well as ANN training without manu…
Dynamic Slicing for Deep Neural Networks
Ziqi Zhang, Yuanchun Li, Yao Guo +2
Program slicing has been widely applied in a variety of software engineering tasks. However, existing program slicing techniques only deal with traditional programs that are constr…
Understanding and Diagnosing Vulnerability under Adversarial Attacks
Haizhong Zheng, Ziqi Zhang, Honglak Lee +1
Deep Neural Networks (DNNs) are known to be vulnerable to adversarial attacks. Currently, there is no clear insight into how slight perturbations cause such a large difference in c…
Adversarial Attacks on Monocular Depth Estimation
Ziqi Zhang, Xinge Zhu, Yingwei Li +2
Recent advances of deep learning have brought exceptional performance on many computer vision tasks such as semantic segmentation and depth estimation. However, the vulnerability o…
Object Relational Graph with Teacher-Recommended Learning for Video Captioning
Ziqi Zhang, Yaya Shi, Chunfeng Yuan +4
Taking full advantage of the information from both vision and language is critical for the video captioning task. Existing models lack adequate visual representation due to the neg…
Efficient Adversarial Training with Transferable Adversarial Examples
Haizhong Zheng, Ziqi Zhang, Juncheng Gu +2
Adversarial training is an effective defense method to protect classification models against adversarial attacks. However, one limitation of this approach is that it can require or…
VATEX Captioning Challenge 2019: Multi-modal Information Fusion and Multi-stage Training Strategy for Video Captioning
Ziqi Zhang, Yaya Shi, Jiutong Wei +3
Multi-modal information is essential to describe what has happened in a video. In this work, we represent videos by various appearance, motion and audio information guided with vid…
Fashion Editing with Adversarial Parsing Learning
Haoye Dong, Xiaodan Liang, Yixuan Zhang +6
Interactive fashion image manipulation, which enables users to edit images with sketches and color strokes, is an interesting research problem with great application value. Existin…