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Found 16 papers, 6 papers with code
CSPCL: Category Semantic Prior Contrastive Learning for Deformable DETR-Based Prohibited Item Detectors
Prohibited item detection based on X-ray images is one of the most effective security inspection methods.
Learning Optimal Combination Patterns for Lightweight Stereo Image Super-Resolution
RWBlock empowers LSNB with the capability to explore various combination patterns of pairwise NAFBlocks by adaptive re-weighting of feature.
Structure Modeling Activation Free Fourier Network for Spacecraft Image Denoising
We present AFFB and utilize an improved Fast Fourier block to extract repetitive periodic features and long-range information in noisy spacecraft image.
Norface: Improving Facial Expression Analysis by Identity Normalization
First, the carefully designed normalization network struggles to directly remove the above task-irrelevant noise, by maintaining facial expression consistency but normalizing all original images to a common identity with consistent pose, and background.
Ranked #1 on
Facial Expression Recognition (FER)
on DISFA
Open-Vocabulary X-ray Prohibited Item Detection via Fine-tuning CLIP
To address aforementioned challenges, in this paper, we introduce distillation-based open-vocabulary object detection (OVOD) task into X-ray security inspection domain by extending CLIP to learn visual representations in our specific X-ray domain, aiming to detect novel prohibited item categories beyond base categories on which the detector is trained.
MMCL: Boosting Deformable DETR-Based Detectors with Multi-Class Min-Margin Contrastive Learning for Superior Prohibited Item Detection
Prohibited Item detection in X-ray images is one of the most effective security inspection methods. However, differing from natural light images, the unique overlapping phenomena in X-ray images lead to the coupling of foreground and background features, thereby lowering the accuracy of general object detectors. Therefore, we propose a Multi-Class Min-Margin Contrastive Learning (MMCL) method that, by clarifying the category semantic information of content queries under the deformable DETR architecture, aids the model in extracting specific category foreground information from coupled features. Specifically, after grouping content queries by the number of categories, we employ the Multi-Class Inter-Class Exclusion (MIE) loss to push apart content queries from different groups.
Emphasizing Crucial Features for Efficient Image Restoration
SFAM consists of two modules: the spatial domain attention module (SDAM) and the frequency domain attention module (FDAM).
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
Leveraging the proposed dataset, we introduce a CLIP-based style encoder that projects natural language-based descriptions to the representations of expressions.
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.
