activity
20182024
most citedSpecNet: Spectral Domain Convolutional Neural Network

8 citations · 9 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024

PA-SAM: Prompt Adapter SAM for High-Quality Image Segmentation

Zhaozhi Xie, Bochen Guan, Weihao Jiang +4

The Segment Anything Model (SAM) has exhibited outstanding performance in various image segmentation tasks. Despite being trained with over a billion masks, SAM faces challenges in…

cs.CV2023

FreeControl: Training-Free Spatial Control of Any Text-to-Image Diffusion Model with Any Condition

Sicheng Mo, Fangzhou Mu, Kuan Heng Lin +4

Recent approaches such as ControlNet offer users fine-grained spatial control over text-to-image (T2I) diffusion models. However, auxiliary modules have to be trained for each type…

cs.CV2023★ 1 cited

Vision Backbone Enhancement via Multi-Stage Cross-Scale Attention

Liang Shang, Yanli Liu, Zhengyang Lou +4

Convolutional neural networks (CNNs) and vision transformers (ViTs) have achieved remarkable success in various vision tasks. However, many architectures do not consider interactio…

cs.CV2023

SimHaze: game engine simulated data for real-world dehazing

Zhengyang Lou, Huan Xu, Fangzhou Mu +7

Deep models have demonstrated recent success in single-image dehazing. Most prior methods consider fully supervised training and learn from paired clean and hazy images, where a ha…

cs.CV2021

SMOF: Squeezing More Out of Filters Yields Hardware-Friendly CNN Pruning

Yanli Liu, Bochen Guan, Qinwen Xu +2

For many years, the family of convolutional neural networks (CNNs) has been a workhorse in deep learning. Recently, many novel CNN structures have been designed to address increasi…

cs.CV2019★ 8 cited

SpecNet: Spectral Domain Convolutional Neural Network

Bochen Guan, Jinnian Zhang, William A. Sethares +2

The memory consumption of most Convolutional Neural Network (CNN) architectures grows rapidly with increasing depth of the network, which is a major constraint for efficient networ…

eess.IV2018

Video Logo Retrieval based on local Features

Bochen Guan, Hanrong Ye, Hong Liu +1

Estimation of the frequency and duration of logos in videos is important and challenging in the advertisement industry as a way of estimating the impact of ad purchases. Since logo…