Scale-covariant and scale-invariant Gaussian derivative networks
Fuente:
arXiv
Guardado en:
| Autor principal: | Lindeberg, Tony |
|---|---|
| Formato: | Preprint |
| Publicado: |
2020
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Scale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with spatial scaling variations
por: Perzanowski, Andrzej, et al.
Publicado: (2024)
por: Perzanowski, Andrzej, et al.
Publicado: (2024)
Scale-invariant Gaussian derivative residual networks
por: Perzanowski, Andrzej, et al.
Publicado: (2026)
por: Perzanowski, Andrzej, et al.
Publicado: (2026)
Provably scale-covariant networks from oriented quasi quadrature measures in cascade
por: Lindeberg, Tony
Publicado: (2019)
por: Lindeberg, Tony
Publicado: (2019)
Provably scale-covariant continuous hierarchical networks based on scale-normalized differential expressions coupled in cascade
por: Lindeberg, Tony
Publicado: (2019)
por: Lindeberg, Tony
Publicado: (2019)
Understanding when spatial transformer networks do not support invariance, and what to do about it
por: Finnveden, Lukas, et al.
Publicado: (2020)
por: Finnveden, Lukas, et al.
Publicado: (2020)
Exploring the ability of CNNs to generalise to previously unseen scales over wide scale ranges
por: Jansson, Ylva, et al.
Publicado: (2020)
por: Jansson, Ylva, et al.
Publicado: (2020)
Unified theory for joint covariance properties under geometric image transformations for spatio-temporal receptive fields according to the generalized Gaussian derivative model for visual receptive fields
por: Lindeberg, Tony
Publicado: (2023)
por: Lindeberg, Tony
Publicado: (2023)
Inability of spatial transformations of CNN feature maps to support invariant recognition
por: Jansson, Ylva, et al.
Publicado: (2020)
por: Jansson, Ylva, et al.
Publicado: (2020)
Relationships between the degrees of freedom in the affine Gaussian derivative model for visual receptive fields and 2-D affine image transformations, with application to covariance properties of simple cells in the primary visual cortex
por: Lindeberg, Tony
Publicado: (2024)
por: Lindeberg, Tony
Publicado: (2024)
Approximation properties relative to continuous scale space for hybrid discretizations of Gaussian derivative operators
por: Lindeberg, Tony
Publicado: (2024)
por: Lindeberg, Tony
Publicado: (2024)
Hybrid Lie semi-group and cascade structures for the generalized Gaussian derivative model for visual receptive fields
por: Lindeberg, Tony
Publicado: (2025)
por: Lindeberg, Tony
Publicado: (2025)
Covariant spatio-temporal receptive fields for spiking neural networks
por: Pedersen, Jens Egholm, et al.
Publicado: (2024)
por: Pedersen, Jens Egholm, et al.
Publicado: (2024)
Discrete approximations of Gaussian smoothing and Gaussian derivatives
por: Lindeberg, Tony
Publicado: (2023)
por: Lindeberg, Tony
Publicado: (2023)
The problems with using STNs to align CNN feature maps
por: Finnveden, Lukas, et al.
Publicado: (2020)
por: Finnveden, Lukas, et al.
Publicado: (2020)
Modelling and analysis of the 8 filters from the "master key filters hypothesis" for depthwise-separable deep networks in relation to idealized receptive fields based on scale-space theory
por: Lindeberg, Tony, et al.
Publicado: (2025)
por: Lindeberg, Tony, et al.
Publicado: (2025)
Scale-covariant spiking wavelets
por: Pedersen, Jens Egholm, et al.
Publicado: (2026)
por: Pedersen, Jens Egholm, et al.
Publicado: (2026)
Neural Gaussian Scale-Space Fields
por: Mujkanovic, Felix, et al.
Publicado: (2024)
por: Mujkanovic, Felix, et al.
Publicado: (2024)
Dreaming up scale invariance via inverse renormalization group
por: Rançon, Adam, et al.
Publicado: (2025)
por: Rançon, Adam, et al.
Publicado: (2025)
Mitigating covariate shift in non-colocated data with learned parameter priors
por: Khan, Behraj, et al.
Publicado: (2024)
por: Khan, Behraj, et al.
Publicado: (2024)
TrashDet: Iterative Neural Architecture Search for Efficient Waste Detection
por: Tran, Tony, et al.
Publicado: (2025)
por: Tran, Tony, et al.
Publicado: (2025)
Confidence-calibrated covariate shift correction for few-shot classification in Vision-Language Models
por: Khan, Behraj, et al.
Publicado: (2025)
por: Khan, Behraj, et al.
Publicado: (2025)
Diffusion-Guided Gaussian Splatting for Large-Scale Unconstrained 3D Reconstruction and Novel View Synthesis
por: Mithun, Niluthpol Chowdhury, et al.
Publicado: (2025)
por: Mithun, Niluthpol Chowdhury, et al.
Publicado: (2025)
Large-Scale High-Quality 3D Gaussian Head Reconstruction from Multi-View Captures
por: Ntavelis, Evangelos, et al.
Publicado: (2026)
por: Ntavelis, Evangelos, et al.
Publicado: (2026)
Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning
por: Rypeść, Grzegorz, et al.
Publicado: (2024)
por: Rypeść, Grzegorz, et al.
Publicado: (2024)
MPCM-Net: Multi-scale network integrates partial attention convolution with Mamba for ground-based cloud image segmentation
por: Niu, Penghui, et al.
Publicado: (2025)
por: Niu, Penghui, et al.
Publicado: (2025)
Forest canopy height estimation from satellite RGB imagery using large-scale airborne LiDAR-derived training data and monocular depth estimation
por: Lai, Yongkang, et al.
Publicado: (2026)
por: Lai, Yongkang, et al.
Publicado: (2026)
ELASTIC: Efficient Once For All Iterative Search for Object Detection on Microcontrollers
por: Tran, Tony, et al.
Publicado: (2025)
por: Tran, Tony, et al.
Publicado: (2025)
VIGS SLAM: IMU-based Large-Scale 3D Gaussian Splatting SLAM
por: Pak, Gyuhyeon, et al.
Publicado: (2025)
por: Pak, Gyuhyeon, et al.
Publicado: (2025)
Diffusion Model Conditioning on Gaussian Mixture Model and Negative Gaussian Mixture Gradient
por: Lu, Weiguo, et al.
Publicado: (2024)
por: Lu, Weiguo, et al.
Publicado: (2024)
Matricial Free Energy as a Gaussianizing Regularizer: Enhancing Autoencoders for Gaussian Code Generation
por: Sonthalia, Rishi, et al.
Publicado: (2025)
por: Sonthalia, Rishi, et al.
Publicado: (2025)
Improving MLLM Historical Record Extraction with Test-Time Image
por: Archibald, Taylor, et al.
Publicado: (2025)
por: Archibald, Taylor, et al.
Publicado: (2025)
ILPO-NET: Network for the invariant recognition of arbitrary volumetric patterns in 3D
por: Zhemchuzhnikov, Dmitrii, et al.
Publicado: (2024)
por: Zhemchuzhnikov, Dmitrii, et al.
Publicado: (2024)
Align Your Gaussians: Text-to-4D with Dynamic 3D Gaussians and Composed Diffusion Models
por: Ling, Huan, et al.
Publicado: (2023)
por: Ling, Huan, et al.
Publicado: (2023)
Cross-Validation Is All You Need: A Statistical Approach To Label Noise Estimation
por: Chen, Jianan, et al.
Publicado: (2023)
por: Chen, Jianan, et al.
Publicado: (2023)
Gaussian Mixture Flow Matching Models
por: Chen, Hansheng, et al.
Publicado: (2025)
por: Chen, Hansheng, et al.
Publicado: (2025)
FreeGaussian: Annotation-free Control of Articulated Objects via 3D Gaussian Splats with Flow Derivatives
por: Chen, Qizhi, et al.
Publicado: (2024)
por: Chen, Qizhi, et al.
Publicado: (2024)
Higher order PCA-like rotation-invariant features for detailed shape descriptors modulo rotation
por: Duda, Jarek
Publicado: (2026)
por: Duda, Jarek
Publicado: (2026)
Epoch-evolving Gaussian Process Guided Learning
por: Cui, Jiabao, et al.
Publicado: (2020)
por: Cui, Jiabao, et al.
Publicado: (2020)
GViT: Representing Images as Gaussians for Visual Recognition
por: Hernandez, Jefferson, et al.
Publicado: (2025)
por: Hernandez, Jefferson, et al.
Publicado: (2025)
Aligned explanations in neural networks
por: Lobet, Corentin, et al.
Publicado: (2026)
por: Lobet, Corentin, et al.
Publicado: (2026)
Ejemplares similares
-
Scale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with spatial scaling variations
por: Perzanowski, Andrzej, et al.
Publicado: (2024) -
Scale-invariant Gaussian derivative residual networks
por: Perzanowski, Andrzej, et al.
Publicado: (2026) -
Provably scale-covariant networks from oriented quasi quadrature measures in cascade
por: Lindeberg, Tony
Publicado: (2019) -
Provably scale-covariant continuous hierarchical networks based on scale-normalized differential expressions coupled in cascade
por: Lindeberg, Tony
Publicado: (2019) -
Understanding when spatial transformer networks do not support invariance, and what to do about it
por: Finnveden, Lukas, et al.
Publicado: (2020)