activity
20142020
most citedObject Detectors Emerge in Deep Scene CNNs

715 citations · 905 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV20201 cited

Multimodal Memorability: Modeling Effects of Semantics and Decay on Video Memorability

Anelise Newman, Camilo Fosco, Vincent Casser +3

A key capability of an intelligent system is deciding when events from past experience must be remembered and when they can be forgotten. Towards this goal, we develop a predictive…

cs.CV2020

We Have So Much In Common: Modeling Semantic Relational Set Abstractions in Videos

Alex Andonian, Camilo Fosco, Mathew Monfort +4

Identifying common patterns among events is a key ability in human and machine perception, as it underlies intelligent decision making. We propose an approach for learning semantic…

cs.CV202010 cited

AR-Net: Adaptive Frame Resolution for Efficient Action Recognition

Yue Meng, Chung-Ching Lin, Rameswar Panda +5

Action recognition is an open and challenging problem in computer vision. While current state-of-the-art models offer excellent recognition results, their computational expense lim…

cs.CV2016175 cited

Places: An Image Database for Deep Scene Understanding

Bolei Zhou, Aditya Khosla, Agata Lapedriza +2

The rise of multi-million-item dataset initiatives has enabled data-hungry machine learning algorithms to reach near-human semantic classification at tasks such as object and scene…

q-bio.NC20164 cited

Grand Challenges for Global Brain Sciences

Joshua T. Vogelstein, Katrin Amunts, Andreas Andreou +59

The next grand challenges for society and science are in the brain sciences. A collection of 60+ scientists from around the world, together with 10+ observers from national, privat…

cs.CV2014715 cited

Object Detectors Emerge in Deep Scene CNNs

Bolei Zhou, Aditya Khosla, Agata Lapedriza +2

With the success of new computational architectures for visual processing, such as convolutional neural networks (CNN) and access to image databases with millions of labeled exampl…