Papers Feature Correlation
“Feature Correlation” 태그가 달린 논문 124편 · 필터 해제
FilterPrompt: A Simple yet Efficient Approach to Guide Image Appearance Transfer in Diffusion Models
In controllable generation tasks, flexibly manipulating the generated images to attain a desired appearance or structure based on a single input image cue remains a critical and longstanding challenge. Achieving this req…
Appearance TransferFeature CorrelationMinimizing Chebyshev Prototype Risk Magically Mitigates the Perils of Overfitting
Overparameterized deep neural networks (DNNs), if not sufficiently regularized, are susceptible to overfitting their training examples and not generalizing well to test data. To discourage overfitting, researchers have d…
Feature CorrelationNeural Image Compression with Quantization Rectifier
Neural image compression has been shown to outperform traditional image codecs in terms of rate-distortion performance. However, quantization introduces errors in the compression process, which can degrade the quality of…
Feature CorrelationImage CompressionImage ReconstructionQuantizationCustomizable Avatars with Dynamic Facial Action Coded Expressions (CADyFACE) for Improved User Engagement
Customizable 3D avatar-based facial expression stimuli may improve user engagement in behavioral biomarker discovery and therapeutic intervention for autism, Alzheimer's disease, facial palsy, and more. However, there is…
Feature CorrelationRoot Causing Prediction Anomalies Using Explainable AI
This paper presents a novel application of explainable AI (XAI) for root-causing performance degradation in machine learning models that learn continuously from user engagement data. In such systems a single feature corr…
Feature CorrelationFeature ImportancePredictionAds Recommendation in a Collapsed and Entangled World
We present Tencent's ads recommendation system and examine the challenges and practices of learning appropriate recommendation representations. Our study begins by showcasing our approaches to preserving prior knowledge …
Feature CorrelationModel OptimizationGraph-Skeleton: ~1% Nodes are Sufficient to Represent Billion-Scale Graph
Due to the ubiquity of graph data on the web, web graph mining has become a hot research spot. Nonetheless, the prevalence of large-scale web graphs in real applications poses significant challenges to storage, computati…
Feature CorrelationGraph MiningNode ClassificationAdversarially Robust Feature Learning for Breast Cancer Diagnosis
Adversarial data can lead to malfunction of deep learning applications. It is essential to develop deep learning models that are robust to adversarial data while accurate on standard, clean data. In this study, we propos…
Deep LearningFeature CorrelationChallenges in Variable Importance Ranking Under Correlation
Variable importance plays a pivotal role in interpretable machine learning as it helps measure the impact of factors on the output of the prediction model. Model agnostic methods based on the generation of "null" feature…
Feature CorrelationInterpretable Machine LearningCorrelation-Embedded Transformer Tracking: A Single-Branch Framework
Developing robust and discriminative appearance models has been a long-standing research challenge in visual object tracking. In the prevalent Siamese-based paradigm, the features extracted by the Siamese-like networks a…
Feature CorrelationObject TrackingVisual Object TrackingUnsupversied feature correlation model to predict breast abnormal variation maps in longitudinal mammograms
Breast cancer continues to be a significant cause of mortality among women globally. Timely identification and precise diagnosis of breast abnormalities are critical for enhancing patient prognosis. In this study, we foc…
Anomaly DetectionFeature CorrelationPrognosisSpecificityMulti-Correlation Siamese Transformer Network with Dense Connection for 3D Single Object Tracking
Point cloud-based 3D object tracking is an important task in autonomous driving. Though great advances regarding Siamese-based 3D tracking have been made recently, it remains challenging to learn the correlation between …
3D Object Tracking3D Single Object TrackingAutonomous DrivingFeature Correlation+1Regenerating Arbitrary Video Sequences with Distillation Path-Finding
If the video has long been mentioned as a widespread visualization form, the animation sequence in the video is mentioned as storytelling for people. Producing an animation requires intensive human labor from skilled pro…
Feature CorrelationCODA: Temporal Domain Generalization via Concept Drift Simulator
In real-world applications, machine learning models often become obsolete due to shifts in the joint distribution arising from underlying temporal trends, a phenomenon known as the "concept drift". Existing works propose…
Domain GeneralizationFeature CorrelationAsymFormer: Asymmetrical Cross-Modal Representation Learning for Mobile Platform Real-Time RGB-D Semantic Segmentation
Understanding indoor scenes is crucial for urban studies. Considering the dynamic nature of indoor environments, effective semantic segmentation requires both real-time operation and high accuracy.To address this, we pro…
Computational EfficiencyFeature Correlationfeature selectionQuantization+4A Probabilistic Model for Data Redundancy in the Feature Domain
In this paper, we use a probabilistic model to estimate the number of uncorrelated features in a large dataset. Our model allows for both pairwise feature correlation (collinearity) and interdependency of multiple featur…
Feature CorrelationUnsupervised Semantic Segmentation Through Depth-Guided Feature Correlation and Sampling
Traditionally, training neural networks to perform semantic segmentation required expensive human-made annotations. But more recently, advances in the field of unsupervised learning have made significant progress on this…
Feature CorrelationSemantic SegmentationUnsupervised Panoptic SegmentationUnsupervised Semantic SegmentationFF-LOGO: Cross-Modality Point Cloud Registration with Feature Filtering and Local to Global Optimization
Cross-modality point cloud registration is confronted with significant challenges due to inherent differences in modalities between different sensors. We propose a cross-modality point cloud registration framework FF-LOG…
Feature Correlationglobal-optimizationPoint Cloud RegistrationR3D3: Dense 3D Reconstruction of Dynamic Scenes from Multiple Cameras
Dense 3D reconstruction and ego-motion estimation are key challenges in autonomous driving and robotics. Compared to the complex, multi-modal systems deployed today, multi-camera systems provide a simpler, low-cost alter…
3D ReconstructionAutonomous DrivingDepth EstimationDepth Prediction+2Boosting Few-shot Action Recognition with Graph-guided Hybrid Matching
Class prototype construction and matching are core aspects of few-shot action recognition. Previous methods mainly focus on designing spatiotemporal relation modeling modules or complex temporal alignment algorithms. Des…
Action RecognitionFeature CorrelationFew-Shot action recognitionFew Shot Action Recognition+1