Search Results for author:
Found 16 papers, 7 papers with code
MetaFBP: Learning to Learn High-Order Predictor for Personalized Facial Beauty Prediction
To this end, we propose a novel MetaFBP framework, in which we devise a universal feature extractor to capture the aesthetic commonality and then optimize to adapt the aesthetic individuality by shifting the decision boundary of the predictor via a meta-learning mechanism.
Parameter Exchange for Robust Dynamic Domain Generalization
The parameters of dynamic networks can be decoupled into a static and a dynamic component, which are designed to learn domain-invariant and domain-specific features, respectively.
Memory-Constrained Semantic Segmentation for Ultra-High Resolution UAV Imagery
Within the domain of UAV imagery analysis, the segmentation of ultra-high resolution images emerges as a substantial and intricate challenge, especially when grappling with the constraints imposed by GPU memory-restricted computational devices.
Monocular BEV Perception of Road Scenes via Front-to-Top View Projection
We propose a front-to-top view projection (FTVP) module, which takes the constraint of cycle consistency between views into account and makes full use of their correlation to strengthen the view transformation and scene understanding.
Dynamic Domain Generalization
Specifically, we leverage a meta-adjuster to twist the network parameters based on the static model with respect to different data from different domains.
Ranked #18 on
Domain Generalization
on DomainNet
Semi-Supervised Domain Generalization with Evolving Intermediate Domain
From this perspective, we introduce a novel paradigm of DG, termed as Semi-Supervised Domain Generalization (SSDG), to explore how the labeled and unlabeled source domains can interact, and establish two settings, including the close-set and open-set SSDG.
Ultra-high Resolution Image Segmentation via Locality-aware Context Fusion and Alternating Local Enhancement
In particular, we introduce a novel locality-aware context fusion based segmentation model to process local patches, where the relevance between local patch and its various contexts are jointly and complementarily utilized to handle the semantic regions with large variations.
Ranked #2 on
Land Cover Classification
on DeepGlobe
Projecting Your View Attentively: Monocular Road Scene Layout Estimation via Cross-View Transformation
Furthermore, our model runs at 35 FPS on a single GPU, which is efficient and applicable for real-time panorama HD map reconstruction.
Autonomous Driving
Monocular Cross-View Road Scene Parsing(Road)
+2
A Homotopy Coordinate Descent Optimization Method for $l_0$-Norm Regularized Least Square Problem
This paper proposes a homotopy coordinate descent (HCD) method to solve the $l_0$-norm regularized least square ($l_0$-LS) problem for compressed sensing, which combine the homotopy technique with a variant of coordinate descent method.
Joint Adaptive Graph and Structured Sparsity Regularization for Unsupervised Feature Selection
After optimized, a subset of optimal features will be selected in group, and the number of selected features will be determined automatically.
Robust Multi-class Feature Selection via $l_{2,0}$-Norm Regularization Minimization
Feature selection is an important data pre-processing in data mining and machine learning, which can reduce feature size without deteriorating model's performance.
An Internal Covariate Shift Bounding Algorithm for Deep Neural Networks by Unitizing Layers' Outputs
The upper bound for the proposed unitization is noise-free and only dominated by the parameter.
Visualizing the Invisible: Occluded Vehicle Segmentation and Recovery
We conduct comparison experiments on this dataset and demonstrate that our model outperforms the state-of-the-art in tasks of recovering segmentation mask and appearance for occluded vehicles.
Enhancement Mask for Hippocampus Detection and Segmentation
Detection and segmentation of the hippocampal structures in volumetric brain images is a challenging problem in the area of medical imaging.
Deformable Object Tracking with Gated Fusion
In addition, we also propose a gated fusion scheme to control how the variations captured by the deformable convolution affect the original appearance.
An Intelligent Extraversion Analysis Scheme from Crowd Trajectories for Surveillance
To our best knowledge, this is the first attempt to analyze individual extraversion of crowd motions based on trajectories.
