Publications (18)
Context Autoencoder for Self-Supervised Representation Learning
Xiaokang Chen, Mingyu Ding, Xiaodi Wang +7
We present a novel masked image modeling (MIM) approach, context autoencoder (CAE), for self-supervised representation pretraining. We pretrain an encoder by making predictions in…
PP-YOLOv2: A Practical Object Detector
Xin Huang, Xinxin Wang, Wenyu Lv +10
Being effective and efficient is essential to an object detector for practical use. To meet these two concerns, we comprehensively evaluate a collection of existing refinements to…
MAFormer: A Transformer Network with Multi-scale Attention Fusion for Visual Recognition
Yunhao Wang, Huixin Sun, Xiaodi Wang +6
Vision Transformer and its variants have demonstrated great potential in various computer vision tasks. But conventional vision transformers often focus on global dependency at a c…
Probabilistic Ranking-Aware Ensembles for Enhanced Object Detections
Mingyuan Mao, Baochang Zhang, David Doermann +5
Model ensembles are becoming one of the most effective approaches for improving object detection performance already optimized for a single detector. Conventional methods directly…
Heterogeneous Generative Knowledge Distillation with Masked Image Modeling
Ziming Wang, Shumin Han, Xiaodi Wang +3
Small CNN-based models usually require transferring knowledge from a large model before they are deployed in computationally resource-limited edge devices. Masked image modeling (M…
Rethinking the Number of Shots in Robust Model-Agnostic Meta-Learning
Xiaoyue Duan, Guoliang Kang, Runqi Wang +4
Robust Model-Agnostic Meta-Learning (MAML) is usually adopted to train a meta-model which may fast adapt to novel classes with only a few exemplars and meanwhile remain robust to a…
CAE v2: Context Autoencoder with CLIP Target
Xinyu Zhang, Jiahui Chen, Junkun Yuan +10
Masked image modeling (MIM) learns visual representation by masking and reconstructing image patches. Applying the reconstruction supervision on the CLIP representation has been pr…
Student-Teacher Feature Pyramid Matching for Anomaly Detection
Guodong Wang, Shumin Han, Errui Ding +1
Anomaly detection is a challenging task and usually formulated as an one-class learning problem for the unexpectedness of anomalies. This paper proposes a simple yet powerful appro…
Prompt Tuning Inversion for Text-Driven Image Editing Using Diffusion Models
Wenkai Dong, Song Xue, Xiaoyue Duan +1
Recently large-scale language-image models (e.g., text-guided diffusion models) have considerably improved the image generation capabilities to generate photorealistic images in va…
PP-YOLO: An Effective and Efficient Implementation of Object Detector
Xiang Long, Kaipeng Deng, Guanzhong Wang +8
Object detection is one of the most important areas in computer vision, which plays a key role in various practical scenarios. Due to limitation of hardware, it is often necessary…
The 1st Tiny Object Detection Challenge:Methods and Results
Xuehui Yu, Zhenjun Han, Yuqi Gong +22
The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a…
Dual-stream Network for Visual Recognition
Mingyuan Mao, Renrui Zhang, Honghui Zheng +6
Transformers with remarkable global representation capacities achieve competitive results for visual tasks, but fail to consider high-level local pattern information in input image…
Oriented Object Detection with Transformer
Teli Ma, Mingyuan Mao, Honghui Zheng +6
Object detection with Transformers (DETR) has achieved a competitive performance over traditional detectors, such as Faster R-CNN. However, the potential of DETR remains largely un…
PAFNet: An Efficient Anchor-Free Object Detector Guidance
Ying Xin, Guanzhong Wang, Mingyuan Mao +5
Object detection is a basic but challenging task in computer vision, which plays a key role in a variety of industrial applications. However, object detectors based on deep learnin…
HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network
Pengcheng Yuan, Shufei Lin, Cheng Cui +5
This paper addresses representational block named Hierarchical-Split Block, which can be taken as a plug-and-play block to upgrade existing convolutional neural networks, improves…
Language-aware Multiple Datasets Detection Pretraining for DETRs
Jing Hao, Song Chen, Xiaodi Wang +1
Pretraining on large-scale datasets can boost the performance of object detectors while the annotated datasets for object detection are hard to scale up due to the high labor cost.…
2nd Place Solution in Google AI Open Images Object Detection Track 2019
Ruoyu Guo, Cheng Cui, Yuning Du +6
We present an object detection framework based on PaddlePaddle. We put all the strategies together (multi-scale training, FPN, Cascade, Dcnv2, Non-local, libra loss) based on ResNe…
Learning from Large-scale Noisy Web Data with Ubiquitous Reweighting for Image Classification
Jia Li, Yafei Song, Jianfeng Zhu +5
Many advances of deep learning techniques originate from the efforts of addressing the image classification task on large-scale datasets. However, the construction of such clean da…