628 citations · 2.1k across the 30 of their papers we have counts for
5 papers · 1 filter
D3D: Distilled 3D Networks for Video Action Recognition
Jonathan C. Stroud, David A. Ross, Chen Sun +2
State-of-the-art methods for video action recognition commonly use an ensemble of two networks: the spatial stream, which takes RGB frames as input, and the temporal stream, which…
Modulated Policy Hierarchies
Alexander Pashevich, Danijar Hafner, James Davidson +2
Solving tasks with sparse rewards is a main challenge in reinforcement learning. While hierarchical controllers are an intuitive approach to this problem, current methods often req…
Actor-Centric Relation Network
Chen Sun, Abhinav Shrivastava, Carl Vondrick +3
Current state-of-the-art approaches for spatio-temporal action localization rely on detections at the frame level and model temporal context with 3D ConvNets. Here, we go one step…
Rethinking the Faster R-CNN Architecture for Temporal Action Localization
Yu-Wei Chao, Sudheendra Vijayanarasimhan, Bryan Seybold +3
We propose TAL-Net, an improved approach to temporal action localization in video that is inspired by the Faster R-CNN object detection framework. TAL-Net addresses three key short…
Object category learning and retrieval with weak supervision
Steven Hickson, Anelia Angelova, Irfan Essa +1
We consider the problem of retrieving objects from image data and learning to classify them into meaningful semantic categories with minimal supervision. To that end, we propose a…