181 citations · 289 across the 6 of their papers we have counts for
12 papers · 1 filter
Imagine Before You Draw: Visual Prompt Engineering for Image Generation
Liyu Jia, Fengda Zhang, Jiachun Pan +7
Incorporating visual semantic representations as an intermediate step before image generation can reduce the modeling difficulty between text and images, thereby improving generati…
NOAH: Learning Pairwise Object Category Attentions for Image Classification
Chao Li, Aojun Zhou, Anbang Yao
A modern deep neural network (DNN) for image classification tasks typically consists of two parts: a backbone for feature extraction, and a head for feature encoding and class pred…
NODI: Out-Of-Distribution Detection with Noise from Diffusion
Jingqiu Zhou, Aojun Zhou, Hongsheng Li
Out-of-distribution (OOD) detection is a crucial part of deploying machine learning models safely. It has been extensively studied with a plethora of methods developed in the liter…
Omni-Dimensional Dynamic Convolution
Chao Li, Aojun Zhou, Anbang Yao
Learning a single static convolutional kernel in each convolutional layer is the common training paradigm of modern Convolutional Neural Networks (CNNs). Instead, recent research i…
Group R-CNN for Weakly Semi-supervised Object Detection with Points
Shilong Zhang, Zhuoran Yu, Liyang Liu +3
We study the problem of weakly semi-supervised object detection with points (WSSOD-P), where the training data is combined by a small set of fully annotated images with bounding bo…
Group Fisher Pruning for Practical Network Compression
Liyang Liu, Shilong Zhang, Zhanghui Kuang +7
Network compression has been widely studied since it is able to reduce the memory and computation cost during inference. However, previous methods seldom deal with complicated stru…