173 citations · 468 across the 20 of their papers we have counts for
22 papers
RoRA: Role-Oriented Regional Allocation for Visual Token Pruning in MLLMs
Qiyanhui Lu, Han Wu, Rongjian Xu +6
Multimodal large language models (MLLMs) encode images as long visual token sequences, making prefilling and KV-cache storage expensive. Existing training-free pruning methods sele…
Pixel Ignores, Superpixel Sees: Adverse Weather Image Restoration via Semantic-Center SSM
Dayu Li, Shihao Zhou, Leizhi Shu +3
Adverse weather image restoration aims to recover clear visibility from degraded images in complex weather conditions. Existing works attempt to address this problem by modeling re…
Cross-Coordinate Correspondence Pruning for Image-to-Point Cloud Registration
Xin Liu, Rong Qin, Huipeng Lin +5
Recent detection-free approaches have shown significant efficacy in image-to-point cloud (I2P) registration by employing a coarse-to-fine matching pipeline. In the coarse stage, do…
ExpoMotion: A Large-Scale Benchmark and A Householder Projection Network for Multi-Exposure Fusion
Yao Liu, Lishen Qu, Shihao Zhou +6
Multi-Exposure Fusion (MEF) effectively extends dynamic range, but practical deployment is hindered by motion-induced ghosting and the scarcity of high-quality dynamic benchmarks.…
Spread Your Wings: A Radial Strip Transformer for Image Deblurring
Duosheng Chen, Shihao Zhou, Jinshan Pan +3
Exploring motion information is important for the motion deblurring task. Recent the window-based transformer approaches have achieved decent performance in image deblurring. Note…
LAKE-RED: Camouflaged Images Generation by Latent Background Knowledge Retrieval-Augmented Diffusion
Pancheng Zhao, Peng Xu, Pengda Qin +5
Camouflaged vision perception is an important vision task with numerous practical applications. Due to the expensive collection and labeling costs, this community struggles with a…
Harmonizing Light and Darkness: A Symphony of Prior-guided Data Synthesis and Adaptive Focus for Nighttime Flare Removal
Lishen Qu, Shihao Zhou, Jinshan Pan +3
Intense light sources often produce flares in captured images at night, which deteriorates the visual quality and negatively affects downstream applications. In order to train an e…
Seeing the Unseen: A Frequency Prompt Guided Transformer for Image Restoration
Shihao Zhou, Jinshan Pan, Jinglei Shi +3
How to explore useful features from images as prompts to guide the deep image restoration models is an effective way to solve image restoration. In contrast to mining spatial relat…
Look-Around Before You Leap: High-Frequency Injected Transformer for Image Restoration
Shihao Zhou, Duosheng Chen, Jinshan Pan +1
Transformer-based approaches have achieved superior performance in image restoration, since they can model long-term dependencies well. However, the limitation in capturing local i…
MCANet: Medical Image Segmentation with Multi-Scale Cross-Axis Attention
Hao Shao, Quansheng Zeng, Qibin Hou +1
Efficiently capturing multi-scale information and building long-range dependencies among pixels are essential for medical image segmentation because of the various sizes and shapes…
Emotion Recognition from Multiple Modalities: Fundamentals and Methodologies
Sicheng Zhao, Guoli Jia, Jufeng Yang +2
Humans are emotional creatures. Multiple modalities are often involved when we express emotions, whether we do so explicitly (e.g., facial expression, speech) or implicitly (e.g.,…
Affective Image Content Analysis: Two Decades Review and New Perspectives
Sicheng Zhao, Xingxu Yao, Jufeng Yang +5
Images can convey rich semantics and induce various emotions in viewers. Recently, with the rapid advancement of emotional intelligence and the explosive growth of visual data, ext…
Multi-Source Domain Adaptation for Object Detection
Xingxu Yao, Sicheng Zhao, Pengfei Xu +1
To reduce annotation labor associated with object detection, an increasing number of studies focus on transferring the learned knowledge from a labeled source domain to another unl…
Computational Emotion Analysis From Images: Recent Advances and Future Directions
Sicheng Zhao, Quanwei Huang, Youbao Tang +4
Emotions are usually evoked in humans by images. Recently, extensive research efforts have been dedicated to understanding the emotions of images. In this chapter, we aim to introd…
Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation
Sicheng Zhao, Xuanbai Chen, Xiangyu Yue +7
Thanks to large-scale labeled training data, deep neural networks (DNNs) have obtained remarkable success in many vision and multimedia tasks. However, because of the presence of d…
Curriculum CycleGAN for Textual Sentiment Domain Adaptation with Multiple Sources
Sicheng Zhao, Yang Xiao, Jiang Guo +5
Sentiment analysis of user-generated reviews or comments on products and services in social networks can help enterprises to analyze the feedback from customers and take correspond…
Emotion-Based End-to-End Matching Between Image and Music in Valence-Arousal Space
Sicheng Zhao, Yaxian Li, Xingxu Yao +4
Both images and music can convey rich semantics and are widely used to induce specific emotions. Matching images and music with similar emotions might help to make emotion percepti…
Bifurcated backbone strategy for RGB-D salient object detection
Yingjie Zhai, Deng-Ping Fan, Jufeng Yang +4
Multi-level feature fusion is a fundamental topic in computer vision. It has been exploited to detect, segment and classify objects at various scales. When multi-level features mee…
An End-to-End Visual-Audio Attention Network for Emotion Recognition in User-Generated Videos
Sicheng Zhao, Yunsheng Ma, Yang Gu +6
Emotion recognition in user-generated videos plays an important role in human-centered computing. Existing methods mainly employ traditional two-stage shallow pipeline, i.e. extrac…
EGNet:Edge Guidance Network for Salient Object Detection
Jia-Xing Zhao, Jiangjiang Liu, Den-Ping Fan +3
Fully convolutional neural networks (FCNs) have shown their advantages in the salient object detection task. However, most existing FCNs-based methods still suffer from coarse obje…
Simultaneous Subspace Clustering and Cluster Number Estimating based on Triplet Relationship
Jie Liang, Jufeng Yang, Ming-Ming Cheng +2
In this paper we propose a unified framework to simultaneously discover the number of clusters and group the data points into them using subspace clustering. Real data distributed…
Learning from Web Data: the Benefit of Unsupervised Object Localization
Xiaoxiao Sun, Liang Zheng, Yu-Kun Lai +1
Annotating a large number of training images is very time-consuming. In this background, this paper focuses on learning from easy-to-acquire web data and utilizes the learned model…