136 citations · 274 across the 11 of their papers we have counts for
11 papers
PP-MobileSeg: Explore the Fast and Accurate Semantic Segmentation Model on Mobile Devices
Shiyu Tang, Ting Sun, Juncai Peng +6
The success of transformers in computer vision has led to several attempts to adapt them for mobile devices, but their performance remains unsatisfactory in some real-world applica…
RAIS: Robust and Accurate Interactive Segmentation via Continual Learning
Yuying Hao, Yi Liu, Juncai Peng +5
Interactive image segmentation aims at segmenting a target region through a way of human-computer interaction. Recent works based on deep learning have achieved excellent performan…
EISeg: An Efficient Interactive Segmentation Tool based on PaddlePaddle
Yuying Hao, Yi Liu, Yizhou Chen +7
In recent years, the rapid development of deep learning has brought great advancements to image and video segmentation methods based on neural networks. However, to unleash the ful…
Exploring the Relationship between Architecture and Adversarially Robust Generalization
Aishan Liu, Shiyu Tang, Siyuan Liang +4
Adversarial training has been demonstrated to be one of the most effective remedies for defending adversarial examples, yet it often suffers from the huge robustness generalization…
PP-Matting: High-Accuracy Natural Image Matting
Guowei Chen, Yi Liu, Jian Wang +11
Natural image matting is a fundamental and challenging computer vision task. It has many applications in image editing and composition. Recently, deep learning-based approaches hav…
PP-LiteSeg: A Superior Real-Time Semantic Segmentation Model
Juncai Peng, Yi Liu, Shiyu Tang +13
Real-world applications have high demands for semantic segmentation methods. Although semantic segmentation has made remarkable leap-forwards with deep learning, the performance of…
PP-HumanSeg: Connectivity-Aware Portrait Segmentation with a Large-Scale Teleconferencing Video Dataset
Lutao Chu, Yi Liu, Zewu Wu +8
As the COVID-19 pandemic rampages across the world, the demands of video conferencing surge. To this end, real-time portrait segmentation becomes a popular feature to replace backg…
EdgeFlow: Achieving Practical Interactive Segmentation with Edge-Guided Flow
Yuying Hao, Yi Liu, Zewu Wu +8
High-quality training data play a key role in image segmentation tasks. Usually, pixel-level annotations are expensive, laborious and time-consuming for the large volume of trainin…
RobustART: Benchmarking Robustness on Architecture Design and Training Techniques
Shiyu Tang, Ruihao Gong, Yan Wang +9
Deep neural networks (DNNs) are vulnerable to adversarial noises, which motivates the benchmark of model robustness. Existing benchmarks mainly focus on evaluating defenses, but th…
Unsupervised domain adaptation via coarse-to-fine feature alignment method using contrastive learning
Shiyu Tang, Peijun Tang, Yanxiang Gong +2
Previous feature alignment methods in Unsupervised domain adaptation(UDA) mostly only align global features without considering the mismatch between class-wise features. In this wo…
Dual Attention Suppression Attack: Generate Adversarial Camouflage in Physical World
Jiakai Wang, Aishan Liu, Zixin Yin +3
Deep learning models are vulnerable to adversarial examples. As a more threatening type for practical deep learning systems, physical adversarial examples have received extensive r…