Search Results for author:
Found 22 papers, 10 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.
Multiple Planar Object Tracking
Specifically, we present a dual-branch network to track the visible part of planar objects, including vertexes and mask.
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
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).
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.
Ordinal Label Distribution Learning
Therefore, we propose a new paradigm, termed ordinal label distribution learning (OLDL).
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.
Emotion Recognition from Multiple Modalities: Fundamentals and Methodologies
In this tutorial, we discuss several key aspects of multi-modal emotion recognition (MER).
Affective Image Content Analysis: Two Decades Review and New Perspectives
Images can convey rich semantics and induce various emotions in viewers.
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.
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.
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.
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.
