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Found 12 papers, 4 papers with code
Submodlib: A Submodular Optimization Library
A recent work has also leveraged submodular functions to propose submodular information measures which have been found to be very useful in solving the problems of guided subset selection and guided summarization.
Submodular Mutual Information for Targeted Data Subset Selection
With the rapid growth of data, it is becoming increasingly difficult to train or improve deep learning models with the right subset of data.
PRISM: A Rich Class of Parameterized Submodular Information Measures for Guided Subset Selection
Examples of such problems include: i)targeted learning, where the goal is to find subsets with rare classes or rare attributes on which the model is underperforming, and ii)guided summarization, where data (e. g., image collection, text, document or video) is summarized for quicker human consumption with specific additional user intent.
How Good is a Video Summary? A New Benchmarking Dataset and Evaluation Framework Towards Realistic Video Summarization
For long videos, human reference summaries necessary for supervised video summarization techniques are difficult to obtain.
A Unified Framework for Generic, Query-Focused, Privacy Preserving and Update Summarization using Submodular Information Measures
We study submodular information measures as a rich framework for generic, query-focused, privacy sensitive, and update summarization tasks.
Realistic Video Summarization through VISIOCITY: A New Benchmark and Evaluation Framework
Thirdly, we demonstrate that in the presence of multiple ground truth summaries (due to the highly subjective nature of the task), learning from a single combined ground truth summary using a single loss function is not a good idea.
Learning From Less Data: A Unified Data Subset Selection and Active Learning Framework for Computer Vision
Supervised machine learning based state-of-the-art computer vision techniques are in general data hungry.
Demystifying Multi-Faceted Video Summarization: Tradeoff Between Diversity,Representation, Coverage and Importance
This paper addresses automatic summarization of videos in a unified manner.
Vis-DSS: An Open-Source toolkit for Visual Data Selection and Summarization
With increasing amounts of visual data being created in the form of videos and images, visual data selection and summarization are becoming ever increasing problems.
A Framework towards Domain Specific Video Summarization
We propose a novel framework for domain specific video summarization.
Learning From Less Data: Diversified Subset Selection and Active Learning in Image Classification Tasks
Supervised machine learning based state-of-the-art computer vision techniques are in general data hungry and pose the challenges of not having adequate computing resources and of high costs involved in human labeling efforts.
A Unified Multi-Faceted Video Summarization System
Most importantly, we also show that we can summarize hours of video data in a few seconds, and our system allows the user to generate summaries of various lengths and types interactively on the fly.
