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Hnerv: A hybrid neural representation for videos
Implicit neural representations store videos as neural networks and have performed well for
vision tasks such as video compression and denoising. With frame index and/or positional …
vision tasks such as video compression and denoising. With frame index and/or positional …
Boosting neural representations for videos with a conditional decoder
Implicit neural representations (INRs) have emerged as a promising approach for video
storage and processing showing remarkable versatility across various video tasks. However …
storage and processing showing remarkable versatility across various video tasks. However …
Nirvana: Neural implicit representations of videos with adaptive networks and autoregressive patch-wise modeling
Abstract Implicit Neural Representations (INR) have recently shown to be powerful tool for
high-quality video compression. However, existing works are limiting as they do not explicitly …
high-quality video compression. However, existing works are limiting as they do not explicitly …
Chop & learn: Recognizing and generating object-state compositions
Recognizing and generating object-state compositions has been a challenging task,
especially when generalizing to unseen compositions. In this paper, we study the task of …
especially when generalizing to unseen compositions. In this paper, we study the task of …
What is point supervision worth in video instance segmentation?
Video instance segmentation (VIS) is a challenging vision task that aims to detect segment
and track objects in videos. Conventional VIS methods rely on densely annotated object …
and track objects in videos. Conventional VIS methods rely on densely annotated object …
Ds-nerv: Implicit neural video representation with decomposed static and dynamic codes
Implicit neural representations for video (NeRV) have recently become a novel way for high-
quality video representation. However existing works employ a single network to represent …
quality video representation. However existing works employ a single network to represent …
Uvis: Unsupervised video instance segmentation
Video instance segmentation requires classifying segmenting and tracking every object
across video frames. Unlike existing approaches that rely on masks boxes or category labels …
across video frames. Unlike existing approaches that rely on masks boxes or category labels …
StegaNeRV: Video Steganography using Implicit Neural Representation
Numerous studies have recently advanced the state-of-the art for representing videos
through an implicit neural network (INR). As these models become increasingly ubiquitous …
through an implicit neural network (INR). As these models become increasingly ubiquitous …
NVRC: Neural video representation compression
Recent advances in implicit neural representation (INR)-based video coding have
demonstrated its potential to compete with both conventional and other learning-based …
demonstrated its potential to compete with both conventional and other learning-based …
Snerv: Spectra-preserving neural representation for video
Neural representation for video (NeRV), which employs a neural network to parameterize
video signals, introduces a novel methodology in video representations. However, existing …
video signals, introduces a novel methodology in video representations. However, existing …