Gustavo Carneiro
48 papers · 2013–2026 · 11 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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Venues
Top co-authors
Research topics
Machine Learning
(31)
Learning Types Β· Machine Learning
(20)
Deep Learning
(18)
Core Methods
(15)
Computer Vision
(13)
Learning Types Β· Deep Learning
(11)
Artificial Intelligence
(10)
Analysis
(8)
Application Areas
(8)
Optimization & Theory
(8)
Architectures
(5)
Bayesian & Probabilistic
(4)
Core AI
(4)
Learning Paradigms
(4)
Healthcare & Medicine
(3)
Keywords
contrastive learning
(4)
noisy label learning
(4)
data augmentation
(4)
deep learning
(3)
semi-supervised learning
(3)
medical image segmentation
(3)
medical imaging
(3)
convolutional neural network
(3)
semantic segmentation
(3)
weakly supervised learning
(3)
multimodal learning
(3)
multi-label classification
(3)
non-rigid segmentation
(3)
few-shot learning
(2)
expectation maximization
(2)
self-supervised learning
(2)
bayesian inference
(2)
image segmentation
(2)
uncertainty quantification
(2)
probabilistic modeling
(2)
Papers
Coverage-Constrained Human-AI Cooperation with Multiple Experts
AAAI 2026
Layer-Wise High-Impact Parameter Ratio Optimization in Post-Training Quantization for Large Language Models
ACL 2026
Reciprocal Teaching: Dynamic Multi-Model Teacher-Student Learning for Multiple Noisy Annotations
WACV 2026
TransPrune: Token Transition Pruning for Efficient Large Vision-Language Model
CVPR 2026
A Novel Perspective for Multi-Modal Multi-Label Skin Lesion Classification
WACV 2025
CLOC: Contrastive Learning for Ordinal Classification with Multi-Margin N-pair Loss
CVPR 2025
Probabilistic Learning to Defer: Handling Missing Expert Annotations and Controlling Workload Distribution
ICLR 2025
Risk Estimation of Knee Osteoarthritis Progression via Predictive Multi-task Modelling from Efficient Diffusion Model using X-ray Images
MICCAI 2025
Bayesian Detector Combination for Object Detection with Crowdsourced Annotations
ECCV 2024
CPM: Class-conditional Prompting Machine for Audio-visual Segmentation
ECCV 2024
Frequency Attention for Knowledge Distillation
WACV 2024
Instance-dependent Noisy-label Learning with Graphical Model Based Noise-rate Estimation
ECCV 2024
ItTakesTwo: Leveraging Peer Representations for Semi-supervised LiDAR Semantic Segmentation
ECCV 2024
Learning to Complement and to Defer to Multiple Users
ECCV 2024
MetaAug: Meta-Data Augmentation for Post-Training Quantization
ECCV 2024
Unraveling Instance Associations: A Closer Look for Audio-Visual Segmentation
CVPR 2024
BoMD: Bag of Multi-label Descriptors for Noisy Chest X-ray Classification
ICCV 2023
Bootstrapping the Relationship Between Images and Their Clean and Noisy Labels
WACV 2023
Instance-Dependent Noisy Label Learning via Graphical Modelling
WACV 2023
Knowing What To Label for Few Shot Microscopy Image Cell Segmentation
WACV 2023
Learning Support and Trivial Prototypes for Interpretable Image Classification
ICCV 2023
Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning
NeurIPS 2023
Multi-Modal Learning With Missing Modality via Shared-Specific Feature Modelling
CVPR 2023
Residual Pattern Learning for Pixel-Wise Out-of-Distribution Detection in Semantic Segmentation
ICCV 2023
ACPL: Anti-Curriculum Pseudo-Labelling for Semi-Supervised Medical Image Classification
CVPR 2022
Deep One-Class Classification via Interpolated Gaussian Descriptor
AAAI 2022
Perturbed and Strict Mean Teachers for Semi-Supervised Semantic Segmentation
CVPR 2022
Pixel-Wise Energy-Biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes
ECCV 2022
Uncertainty-Aware Multi-modal Learning via Cross-Modal Random Network Prediction
ECCV 2022
Domain Generalisation with Domain Augmented Supervised Contrastive Learning (Student Abstract)
AAAI 2021
EvidentialMix: Learning With Combined Open-Set and Closed-Set Noisy Labels
WACV 2021
Probabilistic task modelling for meta-learning
UAI 2021
Weakly-Supervised Video Anomaly Detection With Robust Temporal Feature Magnitude Learning
ICCV 2021
Probabilistic Object Detection: Definition and Evaluation
WACV 2020
Self-Supervised Monocular Trained Depth Estimation Using Self-Attention and Discrete Disparity Volume
CVPR 2020
Uncertainty in Model-Agnostic Meta-Learning using Variational Inference
WACV 2020
A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning
CVPR 2019
Bayesian Generative Active Deep Learning
ICML 2019
Bayesian Semantic Instance Segmentation in Open Set World
ECCV 2018
Multi-modal Cycle-consistent Generalized Zero-Shot Learning
ECCV 2018
A Bayesian Data Augmentation Approach for Learning Deep Models
NeurIPS 2017
Smart Mining for Deep Metric Learning
ICCV 2017
Learning Local Image Descriptors With Deep Siamese and Triplet Convolutional Networks by Minimising Global Loss Functions
CVPR 2016
Robust Optimization for Deep Regression
ICCV 2015
Weakly-Supervised Structured Output Learning With Flexible and Latent Graphs Using High-Order Loss Functions
ICCV 2015
Fully Automated Non-rigid Segmentation with Distance Regularized Level Set Evolution Initialized and Constrained by Deep-structured Inference
CVPR 2014
Non-rigid Segmentation using Sparse Low Dimensional Manifolds and Deep Belief Networks
CVPR 2014
Top-Down Segmentation of Non-rigid Visual Objects Using Derivative-Based Search on Sparse Manifolds
CVPR 2013