Search Results for author:
Found 29 papers, 13 papers with code
BBS-Net: RGB-D Salient Object Detection with a Bifurcated Backbone Strategy Network
In particular, we 1) propose a bifurcated backbone strategy (BBS) to split the multi-level features into teacher and student features, and 2) utilize a depth-enhanced module (DEM) to excavate informative parts of depth cues from the channel and spatial views.
ICFRNet: Image Complexity Prior Guided Feature Refinement for Real-time Semantic Segmentation
In this paper, we leverage image complexity as a prior for refining segmentation features to achieve accurate real-time semantic segmentation.
LAKE-RED: Camouflaged Images Generation by Latent Background Knowledge Retrieval-Augmented Diffusion
Camouflaged vision perception is an important vision task with numerous practical applications.
Spread Your Wings: A Radial Strip Transformer for Image Deblurring
This attention module contains radial strip windows to reweight image features in the polar coordinate, which preserves more useful information in rotation and translation motion together for better recovering the sharp images.
MART: Masked Affective RepresenTation Learning via Masked Temporal Distribution Distillation
Inspired by psychology research and empirical theory we verify that the degree of emotion may vary in different segments of the video thus introducing the sentiment complementary and emotion intrinsic among temporal segments.
Multimodal Emotion Recognition
Multimodal Sentiment Analysis
+2
Adapt or Perish: Adaptive Sparse Transformer with Attentive Feature Refinement for Image Restoration
Meanwhile FRFN employs an enhance-and-ease scheme to eliminate feature redundancy in channels enhancing the restoration of clear latent images.
ExtDM: Distribution Extrapolation Diffusion Model for Video Prediction
Video prediction is a challenging task due to its nature of uncertainty especially for forecasting a long period.
MCANet: Medical Image Segmentation with Multi-Scale Cross-Axis Attention
To process the significant variations of lesion regions or organs in individual sizes and shapes, we also use multiple convolutions of strip-shape kernels with different kernel sizes in each axial attention path to improve the efficiency of the proposed MCA in encoding spatial information.
Weakly Supervised Video Emotion Detection and Prediction via Cross-Modal Temporal Erasing Network
Automatically predicting the emotions of user-generated videos (UGVs) receives increasing interest recently.
Ranked #3 on
Video Emotion Recognition
on Ekman6
DIP: Dual Incongruity Perceiving Network for Sarcasm Detection
The distribution is generated from the latest data stored in the memory bank, which can adaptively model the difference of semantic similarity between sarcastic and non-sarcastic data.
Progressive Neighbor Consistency Mining for Correspondence Pruning
In the end, we develop a Neighbor Consistency Mining Network (NCMNet) for accurately recovering camera poses and identifying inliers.
Probing Sentiment-Oriented Pre-Training Inspired by Human Sentiment Perception Mechanism
Pre-training of deep convolutional neural networks (DCNNs) plays a crucial role in the field of visual sentiment analysis (VSA).
Multiple Planar Object Tracking
Specifically, we present a dual-branch network to track the visible part of planar objects, including vertexes and mask.
Ordinal Label Distribution Learning
Therefore, we propose a new paradigm, termed ordinal label distribution learning (OLDL).
Emotion Recognition from Multiple Modalities: Fundamentals and Methodologies
In this tutorial, we discuss several key aspects of multi-modal emotion recognition (MER).
Multi-Source Domain Adaptation for Object Detection
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 unlabeled target domain.
Affective Image Content Analysis: Two Decades Review and New Perspectives
Images can convey rich semantics and induce various emotions in viewers.
Computational Emotion Analysis From Images: Recent Advances and Future Directions
Recently, extensive research efforts have been dedicated to understanding the emotions of images.
Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation
First, we generate an adapted domain to align the source and target domains on the pixel-level by improving CycleGAN with a multi-scale structured cycle-consistency loss.
Curriculum CycleGAN for Textual Sentiment Domain Adaptation with Multiple Sources
C-CycleGAN transfers source samples at instance-level to an intermediate domain that is closer to the target domain with sentiment semantics preserved and without losing discriminative features.
Emotion-Based End-to-End Matching Between Image and Music in Valence-Arousal Space
In this paper, we study end-to-end matching between image and music based on emotions in the continuous valence-arousal (VA) space.
Bifurcated backbone strategy for RGB-D salient object detection
In particular, first, we propose to regroup the multi-level features into teacher and student features using a bifurcated backbone strategy (BBS).
Ranked #2 on
RGB-D Salient Object Detection
on RGBD135
An End-to-End Visual-Audio Attention Network for Emotion Recognition in User-Generated Videos
Emotion recognition in user-generated videos plays an important role in human-centered computing.
Ranked #4 on
Video Emotion Recognition
on Ekman6
EGNet:Edge Guidance Network for Salient Object Detection
In the second step, we integrate the local edge information and global location information to obtain the salient edge features.
Simultaneous Subspace Clustering and Cluster Number Estimating based on Triplet Relationship
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.
Learning from Web Data: the Benefit of Unsupervised Object Localization
In this work, we first systematically study the built-in gap between the web and standard datasets, i. e. different data distributions between the two kinds of data.
Sub-GAN: An Unsupervised Generative Model via Subspaces
The recent years have witnessed significant growth in constructing robust generative models to capture informative distributions of natural data.
Clinical Skin Lesion Diagnosis Using Representations Inspired by Dermatologist Criteria
Accordingly, we design six medical representations considering different criteria for the recognition of skin lesions, and construct a diagnosis system for clinical skin disease images.
Weakly Supervised Coupled Networks for Visual Sentiment Analysis
The second branch utilizes both the holistic and localized information by coupling the sentiment map with deep features for robust classification.
