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Found 29 papers, 13 papers with code
VIPL-HR: A Multi-modal Database for Pulse Estimation from Less-constrained Face Video
We also learn a deep HR estimator (named as RhythmNet) with the proposed spatial-temporal representation, which achieves promising results on both the public-domain and our VIPL-HR HR estimation databases.
3D U$^2$-Net: A 3D Universal U-Net for Multi-Domain Medical Image Segmentation
Instead of a collection of multiple models, it is highly desirable to learn a universal data representation for different tasks, ideally a single model with the addition of a minimal number of parameters steered to each task.
Deep Learning to Segment Pelvic Bones: Large-scale CT Datasets and Baseline Models
Due to the lack of a large-scale pelvic CT dataset with annotations, deep learning methods are not fully explored.
Video-based Remote Physiological Measurement via Cross-verified Feature Disentangling
Remote physiological measurements, e. g., remote photoplethysmography (rPPG) based heart rate (HR), heart rate variability (HRV) and respiration frequency (RF) measuring, are playing more and more important roles under the application scenarios where contact measurement is inconvenient or impossible.
Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition
In this work, we propose a semi-supervised approach for AU recognition utilizing a large number of web face images without AU labels and a relatively small face dataset with AU annotations inspired by the co-training methods.
FCSR-GAN: Joint Face Completion and Super-resolution via Multi-task Learning
Combined variations containing low-resolution and occlusion often present in face images in the wild, e. g., under the scenario of video surveillance.
DISC: Learning From Noisy Labels via Dynamic Instance-Specific Selection and Correction
Then we propose a dynamic threshold strategy for each instance, based on the momentum of each instance's memorization strength in previous epochs to select and correct noisy labeled data.
Miss the Point: Targeted Adversarial Attack on Multiple Landmark Detection
A comprehensive evaluation on a public dataset for cephalometric landmark detection demonstrates that the adversarial examples generated by ATI-FGSM break the CNN-based network more effectively and efficiently, compared with the original Iterative FGSM attack.
Encoding CT Anatomy Knowledge for Unpaired Chest X-ray Image Decomposition
We hereby propose a decomposition generative adversarial network (DecGAN) to anatomically decompose a CXR image but with unpaired data.
Affective Behaviour Analysis Using Pretrained Model with Facial Priori
As a result, we utilize AffectNet pretrained CNN to extract expression scores concatenating with expression and AU scores from ViT to obtain the final VA features.
Data-Free Knowledge Distillation via Feature Exchange and Activation Region Constraint
Therefore, we propose mSARC to assure the student network can imitate not only the logit output but also the spatial activation region of the teacher network in order to alleviate the influence of unwanted noises in diverse synthetic images on distillation learning.
Decoupled Textual Embeddings for Customized Image Generation
To decouple irrelevant attributes (i. e., background and pose) from the subject embedding, we further present several attribute mappers that encode each image as several image-specific subject-unrelated embeddings.
Modeling the Relative Visual Tempo for Self-supervised Skeleton-based Action Recognition
Specifically, we design a Relative Visual Tempo Learning (RVTL) task to explore the motion information in intra-video clips, and an Appearance-Consistency (AC) task to learn appearance information simultaneously, resulting in more representative spatiotemporal features.
Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach
In DMTL, we tackle attribute correlation and heterogeneity with convolutional neural networks (CNNs) consisting of shared feature learning for all the attributes, and category-specific feature learning for heterogeneous attributes.
Ranked #5 on
Facial Attribute Classification
on LFWA
Tattoo Image Search at Scale: Joint Detection and Compact Representation Learning
To close the gap, we propose an efficient tattoo search approach that is able to learn tattoo detection and compact representation jointly in a single convolutional neural network (CNN) via multi-task learning.
Mean-Variance Loss for Deep Age Estimation From a Face
Age estimation has broad application prospects of many fields, such as video surveillance, social networking, and human-computer interaction.
Ranked #3 on
Age Estimation
on ChaLearn 2016
RhythmNet: End-to-end Heart Rate Estimation from Face via Spatial-temporal Representation
Recently, some methods have been proposed for remote HR estimation from face videos; however, most of them focus on well-controlled scenarios, their generalization ability into less-constrained scenarios (e. g., with head movement, and bad illumination) are not known.
The 1st Challenge on Remote Physiological Signal Sensing (RePSS)
Remote measurement of physiological signals from videos is an emerging topic.
Cross-domain Face Presentation Attack Detection via Multi-domain Disentangled Representation Learning
In light of this, we propose an efficient disentangled representation learning for cross-domain face PAD.
Human Recognition Using Face in Computed Tomography
With the mushrooming use of computed tomography (CT) images in clinical decision making, management of CT data becomes increasingly difficult.
Bounding Maps for Universal Lesion Detection
The bounding maps (BMs) are used in two-stage anchor-based ULD frameworks to reduce the FP rate.
Conditional Training with Bounding Map for Universal Lesion Detection
Universal Lesion Detection (ULD) in computed tomography plays an essential role in computer-aided diagnosis.
Ranked #3 on
Medical Object Detection
on DeepLesion
Where is the disease? Semi-supervised pseudo-normality synthesis from an abnormal image
Pseudo-normality synthesis, which computationally generates a pseudo-normal image from an abnormal one (e. g., with lesions), is critical in many perspectives, from lesion detection, data augmentation to clinical surgery suggestion.
Dual-GAN: Joint BVP and Noise Modeling for Remote Physiological Measurement
Remote photoplethysmography (rPPG) based physiological measurement has great application values in health monitoring, emotion analysis, etc.
Automatic Facial Paralysis Estimation with Facial Action Units
In this paper, we propose a novel Adaptive Local-Global Relational Network (ALGRNet) for facial AU detection and use it to classify facial paralysis severity.
SATr: Slice Attention with Transformer for Universal Lesion Detection
Universal Lesion Detection (ULD) in computed tomography plays an essential role in computer-aided diagnosis.
MGRR-Net: Multi-level Graph Relational Reasoning Network for Facial Action Units Detection
While the region-level feature learning from local face patches features via graph neural network can encode the correlation across different AUs, the pixel-wise and channel-wise feature learning via graph attention network can enhance the discrimination ability of AU features from global face features.
Mixed-order self-paced curriculum learning for universal lesion detection
Most SCL methods commonly adopt a loss-based strategy of estimating data difficulty and deweighting the `hard' samples in the early training stage.
AgeNet: Deeply Learned Regressor and Classifier for Robust Apparent Age Estimation
Another key feature of the proposed AgeNet is that, to avoid the problem of over-fitting on small apparent age training set, we exploit a general-to-specific transfer learning scheme.
Ranked #4 on
Age Estimation
on ChaLearn 2015
