414 citations · 1.1k across the 47 of their papers we have counts for
9 papers · 1 filter
HMM-guided frame querying for bandwidth-constrained video search
Bhairav Chidambaram, Mason McGill, Pietro Perona
We design an agent to search for frames of interest in video stored on a remote server, under bandwidth constraints. Using a convolutional neural network to score individual frames…
PanDA: Panoptic Data Augmentation
Yang Liu, Pietro Perona, Markus Meister
The recently proposed panoptic segmentation task presents a significant challenge of image understanding with computer vision by unifying semantic segmentation and instance segment…
From Google Maps to a Fine-Grained Catalog of Street trees
Steve Branson, Jan Dirk Wegner, David Hall +3
Up-to-date catalogs of the urban tree population are important for municipalities to monitor and improve quality of life in cities. Despite much research on automation of tree mapp…
Anchor Loss: Modulating Loss Scale based on Prediction Difficulty
Serim Ryou, Seong-Gyun Jeong, Pietro Perona
We propose a novel loss function that dynamically rescales the cross entropy based on prediction difficulty regarding a sample. Deep neural network architectures in image classific…
The iWildCam 2019 Challenge Dataset
Sara Beery, Dan Morris, Pietro Perona
Camera Traps (or Wild Cams) enable the automatic collection of large quantities of image data. Biologists all over the world use camera traps to monitor biodiversity and population…
Presence-Only Geographical Priors for Fine-Grained Image Classification
Oisin Mac Aodha, Elijah Cole, Pietro Perona
Appearance information alone is often not sufficient to accurately differentiate between fine-grained visual categories. Human experts make use of additional cues such as where, an…
Synthetic Examples Improve Generalization for Rare Classes
Sara Beery, Yang Liu, Dan Morris +5
The ability to detect and classify rare occurrences in images has important applications - for example, counting rare and endangered species when studying biodiversity, or detectin…
The iWildCam 2018 Challenge Dataset
Sara Beery, Grant van Horn, Oisin Mac Aodha +1
Camera traps are a valuable tool for studying biodiversity, but research using this data is limited by the speed of human annotation. With the vast amounts of data now available it…
Task2Vec: Task Embedding for Meta-Learning
Alessandro Achille, Michael Lam, Rahul Tewari +5
We introduce a method to provide vectorial representations of visual classification tasks which can be used to reason about the nature of those tasks and their relations. Given a d…