46 citations · 127 across the 8 of their papers we have counts for
8 papers · 1 filter
WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation
Jongheon Jeong, Yang Zou, Taewan Kim +3
Visual anomaly classification and segmentation are vital for automating industrial quality inspection. The focus of prior research in the field has been on training custom models f…
SPot-the-Difference Self-Supervised Pre-training for Anomaly Detection and Segmentation
Yang Zou, Jongheon Jeong, Latha Pemula +2
Visual anomaly detection is commonly used in industrial quality inspection. In this paper, we present a new dataset as well as a new self-supervised learning method for ImageNet pr…
Shot Contrastive Self-Supervised Learning for Scene Boundary Detection
Shixing Chen, Xiaohan Nie, David Fan +3
Scenes play a crucial role in breaking the storyline of movies and TV episodes into semantically cohesive parts. However, given their complex temporal structure, finding scene boun…
LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networks
Dongqing Zhang, Jiaolong Yang, Dongqiangzi Ye +1
Although weight and activation quantization is an effective approach for Deep Neural Network (DNN) compression and has a lot of potentials to increase inference speed leveraging bi…
Image Recognition Using Scale Recurrent Neural Networks
Dong-Qing Zhang
Convolutional Neural Network(CNN) has been widely used for image recognition with great success. However, there are a number of limitations of the current CNN based image recogniti…
clcNet: Improving the Efficiency of Convolutional Neural Network using Channel Local Convolutions
Dong-Qing Zhang
Depthwise convolution and grouped convolution has been successfully applied to improve the efficiency of convolutional neural network (CNN). We suggest that these models can be con…
Counting Grid Aggregation for Event Retrieval and Recognition
Zhanning Gao, Gang Hua, Dongqing Zhang +2
Event retrieval and recognition in a large corpus of videos necessitates a holistic fixed-size visual representation at the video clip level that is comprehensive, compact, and yet…
Neural Aggregation Network for Video Face Recognition
Jiaolong Yang, Peiran Ren, Dongqing Zhang +4
This paper presents a Neural Aggregation Network (NAN) for video face recognition. The network takes a face video or face image set of a person with a variable number of face image…