4 citations · 4 across the 2 of their papers we have counts for
6 papers
SALISA: Saliency-based Input Sampling for Efficient Video Object Detection
Babak Ehteshami Bejnordi, Amirhossein Habibian, Fatih Porikli +1
High-resolution images are widely adopted for high-performance object detection in videos. However, processing high-resolution inputs comes with high computation costs, and naive d…
Delta Distillation for Efficient Video Processing
Amirhossein Habibian, Haitam Ben Yahia, Davide Abati +2
This paper aims to accelerate video stream processing, such as object detection and semantic segmentation, by leveraging the temporal redundancies that exist between video frames.…
FrameExit: Conditional Early Exiting for Efficient Video Recognition
Amir Ghodrati, Babak Ehteshami Bejnordi, Amirhossein Habibian
In this paper, we propose a conditional early exiting framework for efficient video recognition. While existing works focus on selecting a subset of salient frames to reduce the co…
Skip-Convolutions for Efficient Video Processing
Amirhossein Habibian, Davide Abati, Taco S. Cohen +1
We propose Skip-Convolutions to leverage the large amount of redundancies in video streams and save computations. Each video is represented as a series of changes across frames and…
Video Compression With Rate-Distortion Autoencoders
Amirhossein Habibian, Ties van Rozendaal, Jakub M. Tomczak +1
In this paper we present a a deep generative model for lossy video compression. We employ a model that consists of a 3D autoencoder with a discrete latent space and an autoregressi…
Learning Variations in Human Motion via Mix-and-Match Perturbation
Mohammad Sadegh Aliakbarian, Fatemeh Sadat Saleh, Mathieu Salzmann +3
Human motion prediction is a stochastic process: Given an observed sequence of poses, multiple future motions are plausible. Existing approaches to modeling this stochasticity typi…