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Found 9 papers, 2 papers with code
AO-DETR: Anti-Overlapping DETR for X-Ray Prohibited Items Detection
Considering the significant overlapping phenomenon in X-ray prohibited item images, we propose an Anti-Overlapping DETR (AO-DETR) based on one of the state-of-the-art general object detectors, DINO.
Towards a Simultaneous and Granular Identity-Expression Control in Personalized Face Generation
We devise a novel diffusion model that can undertake the task of simultaneously face swapping and reenactment.
FlowFace++: Explicit Semantic Flow-supervised End-to-End Face Swapping
The discriminator is shape-aware and relies on a semantic flow-guided operation to explicitly calculate the shape discrepancies between the target and source faces, thus optimizing the face swapping network to generate highly realistic results.
TalkCLIP: Talking Head Generation with Text-Guided Expressive Speaking Styles
In this work, we propose an expression-controllable one-shot talking head method, dubbed TalkCLIP, where the expression in a speech is specified by the natural language.
2D Semantic Segmentation task 3 (25 classes)
Talking Head Generation
Multi-modal Facial Affective Analysis based on Masked Autoencoder
The CVPR 2023 Competition on Affective Behavior Analysis in-the-wild (ABAW) is dedicated to providing high-quality and large-scale Aff-wild2 for the recognition of commonly used emotion representations, such as Action Units (AU), basic expression categories(EXPR), and Valence-Arousal (VA).
FlowFace: Semantic Flow-guided Shape-aware Face Swapping
Unlike most previous methods that focus on transferring the source inner facial features but neglect facial contours, our FlowFace can transfer both of them to a target face, thus leading to more realistic face swapping.
Facial Action Unit Detection and Intensity Estimation from Self-supervised Representation
As a fine-grained and local expression behavior measurement, facial action unit (FAU) analysis (e. g., detection and intensity estimation) has been documented for its time-consuming, labor-intensive, and error-prone annotation.
Transformer-based Multimodal Information Fusion for Facial Expression Analysis
Then, we introduce a transformer-based fusion module that integrates the static vision features and the dynamic multimodal features.
Enhancing Identification of Structure Function of Academic Articles Using Contextual Information
In the research on identifying the structure function of chapters in academic articles, only a few studies used the deep learning model and explored the optimization for feature input.
