22 citations · 102 across the 12 of their papers we have counts for
12 papers
PVG: Progressive Vision Graph for Vision Recognition
Jiafu Wu, Jian Li, Jiangning Zhang +4
Convolution-based and Transformer-based vision backbone networks process images into the grid or sequence structures, respectively, which are inflexible for capturing irregular obj…
Learning from Noisy Labels with Decoupled Meta Label Purifier
Yuanpeng Tu, Boshen Zhang, Yuxi Li +5
Training deep neural networks(DNN) with noisy labels is challenging since DNN can easily memorize inaccurate labels, leading to poor generalization ability. Recently, the meta-lear…
Learning with Noisy labels via Self-supervised Adversarial Noisy Masking
Yuanpeng Tu, Boshen Zhang, Yuxi Li +6
Collecting large-scale datasets is crucial for training deep models, annotating the data, however, inevitably yields noisy labels, which poses challenges to deep learning algorithm…
Rethinking Mobile Block for Efficient Attention-based Models
Jiangning Zhang, Xiangtai Li, Jian Li +7
This paper focuses on developing modern, efficient, lightweight models for dense predictions while trading off parameters, FLOPs, and performance. Inverted Residual Block (IRB) ser…
SCSNet: An Efficient Paradigm for Learning Simultaneously Image Colorization and Super-Resolution
Jiangning Zhang, Chao Xu, Jian Li +4
In the practical application of restoring low-resolution gray-scale images, we generally need to run three separate processes of image colorization, super-resolution, and dows-samp…
LSTC: Boosting Atomic Action Detection with Long-Short-Term Context
Yuxi Li, Boshen Zhang, Jian Li +5
In this paper, we place the atomic action detection problem into a Long-Short Term Context (LSTC) to analyze how the temporal reliance among video signals affect the action detecti…
Analogous to Evolutionary Algorithm: Designing a Unified Sequence Model
Jiangning Zhang, Chao Xu, Jian Li +7
Inspired by biological evolution, we explain the rationality of Vision Transformer by analogy with the proven practical Evolutionary Algorithm (EA) and derive that both of them hav…
ASFD: Automatic and Scalable Face Detector
Bin Zhang, Jian Li, Yabiao Wang +7
In this paper, we propose a novel Automatic and Scalable Face Detector (ASFD), which is based on a combination of neural architecture search techniques as well as a new loss design…
Fast Learning of Temporal Action Proposal via Dense Boundary Generator
Chuming Lin, Jian Li, Yabiao Wang +7
Generating temporal action proposals remains a very challenging problem, where the main issue lies in predicting precise temporal proposal boundaries and reliable action confidence…
Anti-Confusing: Region-Aware Network for Human Pose Estimation
Xuan Cao, Yanhao Ge, Ying Tai +5
In this work, we propose a novel framework named Region-Aware Network (RANet), which learns the ability of anti-confusing in case of heavy occlusion, nearby person and symmetric ap…
Robust Variational Autoencoder
Haleh Akrami, Anand A. Joshi, Jian Li +2
Machine learning methods often need a large amount of labeled training data. Since the training data is assumed to be the ground truth, outliers can severely degrade learned repres…
DSFD: Dual Shot Face Detector
Jian Li, Yabiao Wang, Changan Wang +6
In this paper, we propose a novel face detection network with three novel contributions that address three key aspects of face detection, including better feature learning, progres…