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Found 12 papers, 7 papers with code
Towards More Efficient Depression Risk Recognition via Gait
Gait is a complex form of motion, and hand-crafted gait features often only capture a fraction of the intricate associations between gait and depression risk.
Balanced Representation Learning for Long-tailed Skeleton-based Action Recognition
Secondly, we design a detached action-aware learning schedule to further mitigate the bias in the representation space.
Multiscale Dynamic Graph Representation for Biometric Recognition with Occlusions
Occlusion is a common problem with biometric recognition in the wild.
Exploring Generalizable Distillation for Efficient Medical Image Segmentation
Considering the domain-invariant representative vectors in MSAN, we propose two generalizable knowledge distillation schemes for cross-domain distillation, Dual Contrastive Graph Distillation (DCGD) and Domain-Invariant Cross Distillation (DICD).
Perturbation Inactivation Based Adversarial Defense for Face Recognition
A straightforward approach is to inactivate the adversarial perturbations so that they can be easily handled as general perturbations.
AnyFace: Free-style Text-to-Face Synthesis and Manipulation
AnyFace can achieve high-quality, high-resolution, and high-diversity face synthesis and manipulation results without any constraints on the number and content of input captions.
Toward Accurate and Reliable Iris Segmentation Using Uncertainty Learning
To make further efforts on accurate and reliable iris segmentation, we propose a bilateral self-attention module and design Bilateral Transformer (BiTrans) with hierarchical architecture by exploring spatial and visual relationships.
Learning Instance-level Spatial-Temporal Patterns for Person Re-identification
In this paper, we propose a novel Instance-level and Spatial-Temporal Disentangled Re-ID method (InSTD), to improve Re-ID accuracy.
Ranked #14 on
Person Re-Identification
on DukeMTMC-reID
Recognition Oriented Iris Image Quality Assessment in the Feature Space
The quality metric proposed in this paper can significantly improve the performance of the recognition algorithm while reducing the number of images discarded for recognition, which is advantageous over hand-crafted factors based iris quality assessment methods.
Dynamic Graph Representation for Partially Occluded Biometrics
During dynamic graph matching, we propose a novel strategy to measure the distances of both nodes and adjacent matrixes.
Alignment Free and Distortion Robust Iris Recognition
And illumination variations may cause irregular distortion of iris texture.
Differential Analysis of Directed Networks
The construction stage consistently selects and estimates both common and differential effects by undertaking L1 regularized regression of each endogenous variable against the predicts of other endogenous variables as well as its anchoring exogenous variables.
