3 papers
cs.CV2025
SIEDD: Shared-Implicit Encoder with Discrete Decoders
Vikram Rangarajan, Shishira Maiya, Max Ehrlich +1
Implicit Neural Representations (INRs) offer exceptional fidelity for video compression by learning per-video optimized functions, but their adoption is crippled by impractically s…
cs.CV2024
Latent-INR: A Flexible Framework for Implicit Representations of Videos with Discriminative Semantics
Shishira R Maiya, Anubhav Gupta, Matthew Gwilliam +2
Implicit Neural Networks (INRs) have emerged as powerful representations to encode all forms of data, including images, videos, audios, and scenes. With video, many INRs for video…
cs.CV2024
Explaining the Implicit Neural Canvas: Connecting Pixels to Neurons by Tracing their Contributions
Namitha Padmanabhan, Matthew Gwilliam, Pulkit Kumar +3
The many variations of Implicit Neural Representations (INRs), where a neural network is trained as a continuous representation of a signal, have tremendous practical utility for d…