16 citations · 17 across the 6 of their papers we have counts for
7 papers
TeCoNeRV: Leveraging Temporal Coherence for Compressible Neural Representations for Videos
Namitha Padmanabhan, Matthew Gwilliam, Abhinav Shrivastava
Implicit Neural Representations (INRs) have recently demonstrated impressive performance for video compression. However, since a separate INR must be overfit for each video, scalin…
How to Design and Train Your Implicit Neural Representation for Video Compression
Matthew Gwilliam, Roy Zhang, Namitha Padmanabhan +2
Implicit neural representation (INR) methods for video compression have recently achieved visual quality and compression ratios that are competitive with traditional pipelines. How…
Trajectory-aligned Space-time Tokens for Few-shot Action Recognition
Pulkit Kumar, Namitha Padmanabhan, Luke Luo +2
We propose a simple yet effective approach for few-shot action recognition, emphasizing the disentanglement of motion and appearance representations. By harnessing recent progress…
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…
Do text-free diffusion models learn discriminative visual representations?
Soumik Mukhopadhyay, Matthew Gwilliam, Yosuke Yamaguchi +6
While many unsupervised learning models focus on one family of tasks, either generative or discriminative, we explore the possibility of a unified representation learner: a model w…
Diffusion Models Beat GANs on Image Classification
Soumik Mukhopadhyay, Matthew Gwilliam, Vatsal Agarwal +5
While many unsupervised learning models focus on one family of tasks, either generative or discriminative, we explore the possibility of a unified representation learner: a model w…
Leveraging Bitstream Metadata for Fast, Accurate, Generalized Compressed Video Quality Enhancement
Max Ehrlich, Jon Barker, Namitha Padmanabhan +4
Video compression is a central feature of the modern internet powering technologies from social media to video conferencing. While video compression continues to mature, for many c…