Implicit Neural Representations

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Period ending 2026-09-21

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164 papers

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Enhanced Neural Video Representation Compression across Extreme Complexity and Quality Scales
Jun 26, 2026Ho Man Kwan, Tianhao Peng, Fan Zhang +3Neural Video Codecs Context Compression
ScaLe-INR: Scale and Learn Implicit Neural Representations
Jun 26, 2026Buwaneka Epakanda, Athulya Ratnayake, Pandula Thennakoon +4Spectral Reconstruction Implicit Neural Representations
Calibrated Harmonic Overlaid Implicit Neural Representations for Multi-Dimensional Data
Jun 25, 2026Honghang Chen, Xiujun Zhang, Xiaoli Sun +1Implicit Neural Representations Spectral Reconstruction
PatchINR: Patch-Based Implicit Neural Representations for Efficient and Scalable Inference
Jun 24, 2026Jiachen Ren, Wenyong Zhou, Taiqiang Wu +4Graph Neural Network Inference Implicit Neural Representations
Structuring Sparsity: Block-Sparse Featurizers Capture Visual Concept Manifolds
Jun 23, 2026Thomas Fel, Matthew Kowal, Mozes Jacobs +22Implicit Neural Representations Sparsity
What's in an Earth Embedding? An Explainability Analysis of Location Encoders
Jun 23, 2026Livia Betti, Sebastian Ricke, Ivica Obadic +2Spatial Representation Implicit Neural Representations
Spectral Gating via Damped Oscillations for Adaptive Implicit Neural Representations
Jun 22, 2026Alex Costanzino, Pierluigi Zama Ramirez, Giuseppe Lisanti +1Implicit Neural Representations Oscillatory Dynamics
PaaF: Raising the perceived quality of INR-Based Image Compression
Jun 19, 2026Lorenzo Catania, Dario AllegraLearned Image Compression Ultra-Low Bitrates
Neural Additive and Basis Models with Feature Selection and Interactions
Jun 18, 2026Yasutoshi Kishimoto, Kota Yamanishi, Takuya Matsuda +1Feature Selection Logistic Regression
NeSyCat Torch: A Differentiable Tensor Implementation of Categorical Semantics for Neurosymbolic Learning
Jun 17, 2026Daniel Romero Schellhorn, Till Mossakowski, Björn GehrkeNeuro-Symbolic Framework Inductive Logic Programming
Effects of sparsity and superposition on loss in simple autoencoders
Jun 16, 2026Mriganka Basu Roy Chowdhury, Eric McLaughlin WeinerImproving Sparse Autoencoders Activation Functions
The Importance of Phase in Neural Representations: An Internal Oppenheim-Lim Test of Image Classifiers
Jun 15, 2026Alper YıldırımImage Classification Implicit Neural Representations
Implicit Neural Representations of Individual Behavior
Jun 10, 2026Andrew Kang, Priya NarasimhanReinforcement-Learning Policies Implicit Neural Representations
Kuramoto Attention: Synchronizing Self-Attention on the Torus
Jun 10, 2026Joshua NunleyImplicit Neural Representations
SirenFNO: Efficient and Full Frequency Learning of Fourier Neural Operators
Jun 9, 2026Pengqing Shi, Jie Yin, Stephen Tierney +1Fourier Neural Operators Neural Operators
DD-INR: Dynamics-Driven Implicit Neural Representation for Accelerated Whole-Brain Functional MRI Reconstruction
Jun 9, 2026Qiaoxin Li, Caini Pan, Pierre-Antoine Comby +2Magnetic Resonance Imaging Reconstruction Implicit Neural Representations
RAM: Reachability Across Morphologies
Jun 8, 2026Tim Walter, Xinyu Chen, Jonathan Külz +1Reachability Morphology
Beyond Neural Collapse: Task-Intrinsic Geometry Governs Neural Representations in Modular Arithmetic
Jun 8, 2026Hu Tan, Kuo Gai, Shihua ZhangNeural Collapse Implicit Neural Representations
Directional Linear Separability of Neural Representations: Geometry and Transformations
Jun 7, 2026Yi Wei, Xuan Qi, Suorong Yang +1Separability Implicit Neural Representations
Architecture Shapes Transfer Specificity in Implicit Neural Representations
Jun 5, 2026D Yang EngImplicit Neural Representations Neural Architectures
Jacobi-Anger Method for Deterministic Initialization in Implicit Neural Representation
Jun 4, 2026Mohammed Alsakabi, Kejia Hu, John M. Dolan +1Implicit Neural Representations Multilayer Perceptrons
Texture-preserving implicit neural representation for Cone beam CT truncated reconstruction
Jun 4, 2026Genyuan Zhang, Junyao Wang, Haoran Lan +3Cone-Beam Computed Tomography Tomography
Catastrophic Forgetting as Accessibility Collapse: A Three-Level Framework for Knowledge Persistence in Continual Learning
Jun 4, 2026Ayushman Trivedi, Bhavika MelwaniCatastrophic Forgetting Continual Learning Methods
Quadratic integrate-and-fire neurons exhibit less fragmented loss landscapes and outperform leaky integrate-and-fire neurons in spike-based gradient descent
Jun 2, 2026Carlo Wenig, Raoul-Martin Memmesheimer, Christian KlosSpiking Neural Networks Loss Landscape
Neural Networks Provably Learn Spectral Representations for Group Composition
Jun 2, 2026Jianliang He, Leda Wang, Fengzhuo Zhang +2Implicit Neural Representations Two-Layer Neural Networks
Richer Representations for Neural Algorithmic Reasoning via Auxiliary Reconstruction
May 30, 2026Jiafu Huang, Chao Peng, Chenyang Xu +7Implicit Neural Representations Representation Learning
Rethinking Amortized Neural Representations for High-Resolution Terrain Elevation Data
May 29, 2026Haoan Feng, Xin Xu, Leila De FlorianiImplicit Neural Representations Hyperbolic Learning
MoE-dqINR: A Unified Mixture-of-Experts Implicit Neural Representation Framework for Scan-Specific Dynamic and Quantitative MRI Reconstruction
May 29, 2026Yinzhe Wu, Fanwen Wang, Zhenxuan Zhang +3Magnetic Resonance Imaging Reconstruction Magnetic Resonance Imaging
Supervised Training Rapidly Degrades Early Visual Cortex Alignment Across Biologically Plausible Learning Rules
May 28, 2026Nils LeuteneggerHuman Visual Cortex Spike-Timing-Dependent Plasticity
A Shared Valence Axis Across Modern LLMs and Human EEG: The Saturation Regularity
May 28, 2026Yousef A. Radwan, Xuhui Liu, Kilichbek Haydarov +2Electroencephalography Spatial Super-Resolution Implicit Neural Representations
Faithful Embeddings of Irregular and Asynchronous Data for Online Log-NCDEs
May 28, 2026Benjamin Walker, Alexandre Bloch, Lingyi Yang +2Neural Ordinary Differential Equations Latent Dynamics
Mind-Omni: A Unified Multi-Task Framework for Brain-Vision-Language Modeling via Discrete Diffusion
May 28, 2026Yizhuo Lu, Changde Du, Qingyu Shi +5Brain-Computer Interface Multi--Task Learning
Neural-Behavioral Representation of Natural Whole-body Movement in Monkeys
May 28, 2026Jieshi He, Puzhe Li, Yanan Sui +1Neural Recordings Human Motion
GeRaF: Neural Geometry Reconstruction from Radio Frequency Signals
May 27, 2026Jiachen Lu, Hailan Shanbhag, Haitham Al HassaniehGeometric Reconstruction Radio Frequency
Trajectory Constraints for Imaging Inverse Problems
May 27, 2026Chaoyan Huang, Haijie Yuan, Saiprasad RavishankarIll-Posed Inverse Problem Inverse Problem
NeR-SC: Adapting Neural Video Representation to Screen Content
May 26, 2026Ruohan Shi, Jiaoyan Zhao, Haogang FengNeural Video Codecs Implicit Neural Representations
K-U-KAN: Koopman-Enhanced U-KAN for 3D Dental Reconstruction from a Single Panoramic X-ray Radiograph
May 24, 2026Bikram Keshari Parida, Abhijit Sen, Wonsang YouCone-Beam Computed Tomography 3D Convolutional Neural Networks
NeurIPS: Neuro-anatomical Inductive Priors for Sphere-based Brain Decoding
May 24, 2026Sijin Yu, Zijiao Chen, Zhenyu Yang +7Brain Magnetic Resonance Imaging Anatomical Priors
MindAlign: Bridging EEG, Vision, and Language for Zero-Shot Visual Decoding
May 23, 2026Zexuan Chen, Sichao Liu, Runhao Lu +4Electroencephalography Spatial Super-Resolution Neural Recordings
ImplicitTerrainV2: Wavelet-Guided Spatially Adaptive Neural Terrain Representation
May 21, 2026Haoan Feng, Xin Xu, Leila De FlorianiImplicit Neural Representations Discrete Wavelet Transform
Temporal Coding as a Substrate for Sensorimotor Object Inference: A Spiking Reinterpretation of Thousand Brains Architecture
May 21, 2026Joy BoseSensorimotor Experience Binary Spikes
Stimulus symmetries can confound representational similarity analyses
May 20, 2026Farhad Pashakhanloo, Jacob A. Zavatone-VethSymmetry Implicit Neural Representations
Platonic Representations in the Human Brain: Unsupervised Recovery of Universal Geometry
May 19, 2026Pablo Marcos-Manchón, Rishi Jha, Lluís FuentemillaImplicit Neural Representations Brain Magnetic Resonance Imaging
Nonlocal operator learning for fMRI encoding and decoding tasks
May 19, 2026Andreas Kramer, Saugat Acharya, Alice Giola +1Brain Magnetic Resonance Imaging Implicit Neural Representations
Representability-Aware Neural Networks for Reduced Density Matrices: Application to Fractional Chern Insulators
May 19, 2026Justin B. Hart, Awwab A. Azam, Thomas Li +4Quantum Topological Phases Many-Body Physics
GLUT: 3D Gaussian Lookup Table for Continuous Color Transformation
May 19, 2026Danna Xue, David Serrano-Lozano, Shaolin Su +13D Gaussian Neural Rendering
Efficient coding along the visual hierarchy
May 18, 2026Ananya Passi, Brian S. Robinson, Michael F. BonnerHuman Visual Cortex Visual Perception
Visualizing the Invisible: Generative Visual Grounding Empowers Universal EEG Understanding in MLLMs
May 18, 2026Jun-Yu Pan, Yansen Wang, Enze Zhang +3Electroencephalography Spatial Super-Resolution Explicit Visual Grounding
PySIFT: GPU-Resident Deterministic SIFT for Deep Learning Vision Pipelines
May 18, 2026Sivakumar K. S., Mohammad Daniyalur Rahman, Gopi Raju MattaVision Sensors Cuda
Isolating Nonlinear Independent Sources in fMRI with $β$ -TCVAE Models
May 15, 2026Qiang Li, Shujian Yu, Jesus Malo +3Brain Magnetic Resonance Imaging Human Brain Networks
From Layers to Networks: Comparing Neural Representations via Diffusion Geometry
May 15, 2026Atharva Khandait, Jan E. GerkenImplicit Neural Representations
Mechanistically Interpretable Neural Encoding Reveals Fine-Grained Functional Selectivity in Human Visual Cortex
May 15, 2026Idan Daniel Grosbard, Mor Geva, Galit YovelHuman Visual Cortex Implicit Neural Representations
How Data Augmentation Shapes Neural Representations
May 14, 2026Tianxiao He, Alex H. Williams, Sarah E. HarveyImplicit Neural Representations Deep Network
Generative Motion In-betweening by Diffusion over Continuous Implicit Representations
May 12, 2026Shiyu Fan, Paul Henderson, Edmond S. L. HoLatent Diffusion Model Keyframe Selection
Spectral Energy Centroid: a Metric for Improving Performance and Analyzing Spectral Bias in Implicit Neural Representations
May 12, 2026Tomasz Dądela, Adam Kania, Maciej Rut +1Implicit Neural Representations High-Fidelity
Deep Minds and Shallow Probes
May 12, 2026Su Hyeong Lee, Risi KondorImplicit Neural Representations Hidden States
Implicit Neural Optimal Transport via Fixed-Point Optimization
May 11, 2026Yesom Park, Eric Gelphman, Stanley Osher +1Optimal Transport Neural Network Optimization
INFANiTE: Implicit Neural representation for high-resolution Fetal brain spatio-temporal Atlas learNing from clinical Thick-slicE MRI
May 11, 2026Xiaotian Hu, Mingxuan Liu, Hongjia Yang +10Brain Magnetic Resonance Imaging Implicit Neural Representations
WindINR: Latent-State INR for Fast Local Wind Query and Correction in Complex Terrain
May 10, 2026Yi Xiao, Qilong Jia, Hang Fan +4Urban Wind State Estimation
HyNeuralMap: Hyperbolic Mapping of Visual Semantics to Neural Hierarchies
May 10, 2026Zihan Ma, Tian Xia, Kexin Wang +3Visual Semantics Hyperbolic Space

Jun 26, 2026 · eess.IVJ/K move · Enter open · S save

Enhanced Neural Video Representation Compression across Extreme Complexity and Quality Scales

Ho Man Kwan, Tianhao Peng, Fan Zhang, Mike Nilsson+2

Visual Information Lab, University of Bristol, UK · Network Connectivity Services Research, BT, UK

Implicit neural representations (INRs) have recently emerged as a promising approach to video compression, delivering competitive rate-distortion performance alongside rapid decoding. However, existing neural video codecs struggle to balance complexity and scalability. Lightweight models often suffer from degraded compression performance when scaled to different bitrate/quality levels, whereas high-performance models exhibit limited scalability, as their model complexity typically increases with quality. This lack of a unified architecture capable of maintaining consistent complexity across a wide range of bitrates severely limits their diverse real-world deployment. To address these challenges, we introduce NVRC++, a novel INR-based video codec that utilizes a lightweight INR with multiple high-resolution feature grids, providing high scalability at any given complexity level. This is paired with an optimization framework that enables efficient overfitting on high-resolution grids for long video sequences, thereby exploiting spatio-temporal redundancies without prohibitive computational or memory overhead. Additionally, an advanced entropy model is designed for efficiently compressing the high-dimensional grid parameters. As a result, NVRC++ provides four complexity levels (from 7kMACs/pixel to 360kMACs/pixel), each spanning wide bitrate and quality ranges while supporting real-time decoding. The experimental results show that NVRC++ offers a much faster decoding speed (up to 7.6x) compared to the SOTA INR-based video codec, NVRC, while delivering comparable performance.

Neural Video Codecs Context Compression Implicit Neural Representations Mean Opinion Scores

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