Nick Barnes
37 papers · 2013–2026 · 8 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (13) π Conference Polyglot (8) π§ Keyword Pioneer π Interdisciplinary Bridge π Cross-Pollinator (6)
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Cross-Pollinator
(6)
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Renaissance Researcher
(5)
πΊοΈ
Taxonomy Completionist
(63)
π§¬
Topic Evolution
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Dynamic Duo
(12)
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Deep Specialist
(12)
β‘
Prolific Year
(8)
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Conference Pioneer
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Century Club
(37)
ποΈ
Keyword Collector
(180)
π₯
Unstoppable
(9)
β
The Questioner
Conferences
CVPR (11)
WACV (10)
ICCV (5)
AAAI (3)
ECCV (3)
NIPS (3)
EMNLP (1)
ICLR (1)
Top co-authors
Keywords
semantic segmentation
(7)
convolutional neural network
(4)
weakly supervised learning
(3)
3d vision
(3)
object detection
(3)
feature learning
(3)
uncertainty estimation
(3)
label shift
(2)
image reconstruction
(2)
generative model
(2)
multimodal learning
(2)
neural network architecture
(2)
multi-modal learning
(2)
markov chain monte carlo
(2)
point cloud
(2)
model calibration
(2)
image segmentation
(2)
domain adaptation
(2)
langevin dynamics
(2)
self-supervised learning
(2)
Papers
False Alarm Rectification for Early Smoke Segmentation
WACV 2026
DermEVAL: A Dermatologist-Reviewed Benchmark for Multimodal Large Language Models
WACV 2026
SmokeBench: Evaluating Multimodal Large Language Models for Wildfire Smoke Detection
WACV 2026
AusSmoke meets MultiNatSmoke: a fully-labelled diverse smoke segmentation dataset
WACV 2026
Open Set Label Shift with Test Time Out-of-Distribution Reference
CVPR 2025
LAM3D: Large Image-Point Clouds Alignment Model for 3D Reconstruction from Single Image
NIPS 2024
Label Shift Estimation for Class-Imbalance Problem: A Bayesian Approach
WACV 2024
Self-Calibrating Vicinal Risk Minimisation for Model Calibration
CVPR 2024
P2C: Self-Supervised Point Cloud Completion from Single Partial Clouds
ICCV 2023
Learning Audio-Visual Source Localization via False Negative Aware Contrastive Learning
CVPR 2023
Model Calibration in Dense Classification with Adaptive Label Perturbation
ICCV 2023
Modeling Aleatoric Uncertainty for Camouflaged Object Detection
WACV 2022
The Devil in Linear Transformer
EMNLP 2022
Energy-Based Generative Cooperative Saliency Prediction
AAAI 2022
Inferring the Class Conditional Response Map for Weakly Supervised Semantic Segmentation
WACV 2022
Transmission-Guided Bayesian Generative Model for Smoke Segmentation
AAAI 2022
Learning Generative Vision Transformer with Energy-Based Latent Space for Saliency Prediction
NIPS 2021
Rethinking conditional GAN training: An approach using geometrically structured latent manifolds
NIPS 2021
Simultaneously Localize, Segment and Rank the Camouflaged Objects
CVPR 2021
Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion
CVPR 2021
Weakly Supervised Video Salient Object Detection
CVPR 2021
RGB-D Saliency Detection via Cascaded Mutual Information Minimization
ICCV 2021
Conditional Generative Modeling via Learning the Latent Space
ICLR 2021
Dense-Resolution Network for Point Cloud Classification and Segmentation
WACV 2021
From Depth What Can You See? Depth Completion via Auxiliary Image Reconstruction
CVPR 2020
UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders
CVPR 2020
Learning Noise-Aware Encoder-Decoder from Noisy Labels by Alternating Back-Propagation for Saliency Detection
ECCV 2020
Blended Convolution and Synthesis for Efficient Discrimination of 3D Shapes
WACV 2020
Fast Image Reconstruction with an Event Camera
WACV 2020
Improved Visual-Semantic Alignment for Zero-Shot Object Detection
AAAI 2020
Reducing the Sim-to-Real Gap for Event Cameras
ECCV 2020
Unsupervised Primitive Discovery for Improved 3D Generative Modeling
CVPR 2019
Transductive Learning for Zero-Shot Object Detection
ICCV 2019
Real Image Denoising With Feature Attention
ICCV 2019
Deep Texture and Structure Aware Filtering Network for Image Smoothing
ECCV 2018
Local Background Enclosure for RGB-D Salient Object Detection
CVPR 2016
Learning Structured Hough Voting for Joint Object Detection and Occlusion Reasoning
CVPR 2013