no code implementations • 26 Mar 2024 • Qiqi Hou, Farzad Farhadzadeh, Amir Said, Guillaume Sautiere, Hoang Le
The rise of new video modalities like virtual reality or autonomous driving has increased the demand for efficient multi-view video compression methods, both in terms of rate-distortion (R-D) performance and in terms of delay and runtime.
no code implementations • 1 Dec 2023 • Amir Said, Hoang Le, Farzad Farhadzadeh
Video compression systems must support increasing bandwidth and data throughput at low cost and power, and can be limited by entropy coding bottlenecks.
no code implementations • 2 Oct 2023 • Ties van Rozendaal, Tushar Singhal, Hoang Le, Guillaume Sautiere, Amir Said, Krishna Buska, Anjuman Raha, Dimitris Kalatzis, Hitarth Mehta, Frank Mayer, Liang Zhang, Markus Nagel, Auke Wiggers
This work presents the first neural video codec that decodes 1080p YUV420 video in real time on a mobile device.
no code implementations • 20 Jan 2023 • Amir Said, Reza Pourreza, Hoang Le
Neural-based image and video codecs are significantly more power-efficient when weights and activations are quantized to low-precision integers.
no code implementations • 8 Aug 2022 • Reza Pourreza, Hoang Le, Amir Said, Guillaume Sautiere, Auke Wiggers
In video compression, coding efficiency is improved by reusing pixels from previously decoded frames via motion and residual compensation.
no code implementations • 18 Jul 2022 • Hoang Le, Liang Zhang, Amir Said, Guillaume Sautiere, Yang Yang, Pranav Shrestha, Fei Yin, Reza Pourreza, Auke Wiggers
Realizing the potential of neural video codecs on mobile devices is a big technological challenge due to the computational complexity of deep networks and the power-constrained mobile hardware.
no code implementations • 31 Mar 2022 • Florian Tramèr, Reza Shokri, Ayrton San Joaquin, Hoang Le, Matthew Jagielski, Sanghyun Hong, Nicholas Carlini
We show that an adversary who can poison a training dataset can cause models trained on this dataset to leak significant private details of training points belonging to other parties.
1 code implementation • CVPR 2020 • Hoang Le, Feng Liu, Shu Zhang, Aseem Agarwala
We then develop a multi-scale neural network and show that when properly trained using our new dataset, this neural network can already handle dynamic scenes to some extent.
no code implementations • ECCV 2018 • Hoang Le, Long Mai, Brian Price, Scott Cohen, Hailin Jin, Feng Liu
Instead of relying on pre-defined low-level image features, our method adaptively predicts object boundaries according to image content and user interactions.
no code implementations • 2 Feb 2017 • Riccardo Zucca, Xerxes D. Arsiwalla, Hoang Le, Mikail Rubinov, Paul Verschure
We test for the power-law, exponential, log-normal and generalized Pareto distributions.