Search Results for author:
Found 19 papers, 8 papers with code
TAB: Text-Align Anomaly Backbone Model for Industrial Inspection Tasks
The proposed anomaly backbone provides a foundation model for more precise anomaly detection and localization.
KFC: Kinship Verification with Fair Contrastive Loss and Multi-Task Learning
Kinship verification is an emerging task in computer vision with multiple potential applications.
ReST: A Reconfigurable Spatial-Temporal Graph Model for Multi-Camera Multi-Object Tracking
Experimental results show that the proposed graph model is able to extract more discriminating features for object tracking, and our model achieves state-of-the-art performance on several public datasets.
Ranked #4 on
Multi-Object Tracking
on Wildtrack
A Closer Look at Geometric Temporal Dynamics for Face Anti-Spoofing
Face anti-spoofing (FAS) is indispensable for a face recognition system.
Interaction-Aware Prompting for Zero-Shot Spatio-Temporal Action Detection
Finally, we calculate the similarity between the interaction feature and the text feature for each label to determine the action category.
Kinship Representation Learning with Face Componential Relation
Kinship recognition aims to determine whether the subjects in two facial images are kin or non-kin, which is an emerging and challenging problem.
Generalized Face Anti-Spoofing via Multi-Task Learning and One-Side Meta Triplet Loss
With the increasing variations of face presentation attacks, model generalization becomes an essential challenge for a practical face anti-spoofing system.
MixFairFace: Towards Ultimate Fairness via MixFair Adapter in Face Recognition
In this paper, we propose MixFairFace framework to improve the fairness in face recognition models.
Holistic Interaction Transformer Network for Action Detection
Actions are about how we interact with the environment, including other people, objects, and ourselves.
Ranked #1 on
Action Detection
on MultiSports
Extremely Low-light Image Enhancement with Scene Text Restoration
Deep learning-based methods have made impressive progress in enhancing extremely low-light images - the image quality of the reconstructed images has generally improved.
PatchNet: A Simple Face Anti-Spoofing Framework via Fine-Grained Patch Recognition
Previous works leverage auxiliary pixel-level supervision and domain generalization approaches to address unseen spoof types.
Local-Adaptive Face Recognition via Graph-based Meta-Clustering and Regularized Adaptation
Leveraging the environment-specific local data after the deployment of the initial global model, LaFR aims at getting optimal performance by training local-adapted models automatically and un-supervisely, as opposed to fixing their initial global model.
FedFR: Joint Optimization Federated Framework for Generic and Personalized Face Recognition
Current state-of-the-art deep learning based face recognition (FR) models require a large number of face identities for central training.
High-Accuracy RGB-D Face Recognition via Segmentation-Aware Face Depth Estimation and Mask-Guided Attention Network
Our DepthNet is used to augment a large 2D face image dataset to a large RGB-D face dataset, which is used for training an accurate RGB-D face recognition model.
Disentangled Representation with Dual-stage Feature Learning for Face Anti-spoofing
Unlike previous FAS disentanglement works with one-stage architecture, we found that the dual-stage training design can improve the training stability and effectively encode the features to detect unseen attack types.
ByeGlassesGAN: Identity Preserving Eyeglasses Removal for Face Images
In this paper, we propose a novel image-to-image GAN framework for eyeglasses removal, called ByeGlassesGAN, which is used to automatically detect the position of eyeglasses and then remove them from face images.
Multimedia
Unified Representation Learning for Cross Model Compatibility
We propose a unified representation learning framework to address the Cross Model Compatibility (CMC) problem in the context of visual search applications.
AugGAN: Cross Domain Adaptation with GAN-based Data Augmentation
Deep learning based image-to-image translation methods aim at learning the joint distribution of the two domains and finding transformations between them.
Ranked #33 on
Link Prediction
on WN18
Non-Rigid Registration of Images With Geometric and Photometric Deformation by Using Local Affine Fourier-Moment Matching
Registration between images taken with different cameras, from different viewpoints or under different lighting conditions is a challenging problem.
