Affective image content analysis: Two decades review and new perspectives
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 …
the rapid advancement of emotional intelligence and the explosive growth of visual data …
Occluded prohibited items detection: An x-ray security inspection benchmark and de-occlusion attention module
Security inspection often deals with a piece of baggage or suitcase where objects are
heavily overlapped with each other, resulting in an unsatisfactory performance for prohibited …
heavily overlapped with each other, resulting in an unsatisfactory performance for prohibited …
Autodir: Automatic all-in-one image restoration with latent diffusion
We present AutoDIR, an innovative all-in-one image restoration system incorporating latent
diffusion. AutoDIR excels in its ability to automatically identify and restore images suffering …
diffusion. AutoDIR excels in its ability to automatically identify and restore images suffering …
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. Existing methods mainly employ traditional two-stage shallow pipeline, ie …
computing. Existing methods mainly employ traditional two-stage shallow pipeline, ie …
WSCNet: Weakly supervised coupled networks for visual sentiment classification and detection
Automatic assessment of sentiment from visual content has gained considerable attention
with the increasing tendency of expressing opinions online. In this paper, we solve the …
with the increasing tendency of expressing opinions online. In this paper, we solve the …
Affective computing for large-scale heterogeneous multimedia data: A survey
The wide popularity of digital photography and social networks has generated a rapidly
growing volume of multimedia data (ie, images, music, and videos), resulting in a great …
growing volume of multimedia data (ie, images, music, and videos), resulting in a great …
Specific class center guided deep hashing for cross-modal retrieval
Z Shu, Y Bai, D Zhang, J Yu, Z Yu, XJ Wu - Information sciences, 2022 - Elsevier
Hashing approaches show excellent retrieval efficiency and low storage usage in search
tasks. In general, most existing deep hashing approaches mainly focus on constructing the …
tasks. In general, most existing deep hashing approaches mainly focus on constructing the …
Looking into gait for perceiving emotions via bilateral posture and movement graph convolutional networks
Emotions can be perceived from a person's gait, ie, their walking style. Existing methods on
gait emotion recognition mainly leverage the posture information as input, but ignore the …
gait emotion recognition mainly leverage the posture information as input, but ignore the …
PDANet: Polarity-consistent deep attention network for fine-grained visual emotion regression
Existing methods on visual emotion analysis mainly focus on coarse-grained emotion
classification, ie assigning an image with a dominant discrete emotion category. However …
classification, ie assigning an image with a dominant discrete emotion category. However …
Deep cross-modal hashing with hashing functions and unified hash codes jointly learning
Due to their high retrieval efficiency and low storage cost, cross-modal hashing methods
have attracted considerable attention. Generally, compared with shallow cross-modal …
have attracted considerable attention. Generally, compared with shallow cross-modal …