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Found 15 papers, 4 papers with code
AUD-TGN: Advancing Action Unit Detection with Temporal Convolution and GPT-2 in Wild Audiovisual Contexts
Leveraging the synergy of both audio data and visual data is essential for understanding human emotions and behaviors, especially in in-the-wild setting.
Multimodal Fusion Method with Spatiotemporal Sequences and Relationship Learning for Valence-Arousal Estimation
This paper presents our approach for the VA (Valence-Arousal) estimation task in the ABAW6 competition.
Exploring Facial Expression Recognition through Semi-Supervised Pretraining and Temporal Modeling
Facial Expression Recognition (FER) plays a crucial role in computer vision and finds extensive applications across various fields.
Facial Expression Recognition
Facial Expression Recognition (FER)
SAR2EO: A High-resolution Image Translation Framework with Denoising Enhancement
Synthetic Aperture Radar (SAR) to electro-optical (EO) image translation is a fundamental task in remote sensing that can enrich the dataset by fusing information from different sources.
A Dual Branch Network for Emotional Reaction Intensity Estimation
Emotional Reaction Intensity(ERI) estimation is an important task in multimodal scenarios, and has fundamental applications in medicine, safe driving and other fields.
Exploring Large-scale Unlabeled Faces to Enhance Facial Expression Recognition
Facial Expression Recognition (FER) is an important task in computer vision and has wide applications in human-computer interaction, intelligent security, emotion analysis, and other fields.
Local Region Perception and Relationship Learning Combined with Feature Fusion for Facial Action Unit Detection
Human affective behavior analysis plays a vital role in human-computer interaction (HCI) systems.
Micro Expression Generation with Thin-plate Spline Motion Model and Face Parsing
We (Team: USTC-IAT-United) also compare our method with other competitors' in MEGC2022, and the expert evaluation results show that our method performs best, which verifies the effectiveness of our method.
Facial Expression Spotting Based on Optical Flow Features
The purpose of micro expression (ME) and macro expression (MaE) spotting task is to locate the onset and offset frames of MaE and ME clips.
Bag of Tricks and a Strong Baseline for FGVC
This motivates us to explore the impact of different methods and components in fine-grained classification on FungiCLEF 2022.
A viable framework for semi-supervised learning on realistic dataset
Semi-supervised Fine-Grained Recognition is a challenging task due to the difficulty of data imbalance, high inter-class similarity and domain mismatch.
BiSTF: Bilateral-Branch Self-Training Framework for Semi-Supervised Large-scale Fine-Grained Recognition
Semi-supervised Fine-Grained Recognition is a challenge task due to the difficulty of data imbalance, high inter-class similarity and domain mismatch.
Deep Fusion Siamese Network for Automatic Kinship Verification
Recognizing Families In the Wild (RFIW) is a challenging kinship recognition task with multiple tracks, which is based on Families in the Wild (FIW), a large-scale and comprehensive image database for automatic kinship recognition.
Retrieval of Family Members Using Siamese Neural Network
While in inference procedure, we try another similarity computing method by dropping the followed several fully connected layers and directly computing the cosine similarity of the two feature vectors.
Grand Challenge of 106-Point Facial Landmark Localization
However, previous competitions on facial landmark localization (i. e., the 300-W, 300-VW and Menpo challenges) aim to predict 68-point landmarks, which are incompetent to depict the structure of facial components.
