Mart: Masked affective representation learning via masked temporal distribution distillation
Limited training data is a long-standing problem for video emotion analysis (VEA). Existing
works leverage the power of large-scale image datasets for transferring while failing to …
works leverage the power of large-scale image datasets for transferring while failing to …
Adapt or perish: Adaptive sparse transformer with attentive feature refinement for image restoration
Transformer-based approaches have achieved promising performance in image restoration
tasks given their ability to model long-range dependencies which is crucial for recovering …
tasks given their ability to model long-range dependencies which is crucial for recovering …
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. To model the temporal dynamics advanced methods benefit from …
forecasting a long period. To model the temporal dynamics advanced methods benefit from …
Lake-red: Camouflaged images generation by latent background knowledge retrieval-augmented diffusion
Camouflaged vision perception is an important vision task with numerous practical
applications. Due to the expensive collection and labeling costs this community struggles …
applications. Due to the expensive collection and labeling costs this community struggles …
Ordinal label distribution learning
C Wen, X Zhang, X Yao, J Yang - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
Label distribution learning (LDL) is a recent hot topic, in which ambiguity is modeled via
description degrees of the labels. However, in common LDL tasks, eg, age estimation, labels …
description degrees of the labels. However, in common LDL tasks, eg, age estimation, labels …
Joint learning of video scene detection and annotation via multi-modal adaptive context network
The tasks of scene detection and annotation have gained impressive attention for
understanding video content. The main challenges lie in mitigating the error propagation of …
understanding video content. The main challenges lie in mitigating the error propagation of …
Hypergraph Multi-modal Large Language Model: Exploiting EEG and Eye-tracking Modalities to Evaluate Heterogeneous Responses for Video Understanding
Understanding of video creativity and content often varies among individuals, with
differences in focal points and cognitive levels across different ages, experiences, and …
differences in focal points and cognitive levels across different ages, experiences, and …
Going Beyond Closed Sets: A Multimodal Perspective for Video Emotion Analysis
Emotion analysis plays a crucial role in understanding video content. Existing studies often
approach it as a closed set classification task, which overlooks the important fact that the …
approach it as a closed set classification task, which overlooks the important fact that the …
eMotions: A Large-Scale Dataset for Emotion Recognition in Short Videos
Nowadays, short videos (SVs) are essential to information acquisition and sharing in our life.
The prevailing use of SVs to spread emotions leads to the necessity of emotion recognition …
The prevailing use of SVs to spread emotions leads to the necessity of emotion recognition …
Facial Affective Behavior Analysis with Instruction Tuning
Facial affective behavior analysis (FABA) is crucial for understanding human mental states
from images. However, traditional approaches primarily deploy models to discriminate …
from images. However, traditional approaches primarily deploy models to discriminate …