209 citations · 621 across the 10 of their papers we have counts for
11 papers
Attentional Pooling for Action Recognition
Rohit Girdhar, Deva Ramanan
We introduce a simple yet surprisingly powerful model to incorporate attention in action recognition and human object interaction tasks. Our proposed attention module can be traine…
Learning Policies for Adaptive Tracking with Deep Feature Cascades
Chen Huang, Simon Lucey, Deva Ramanan
Visual object tracking is a fundamental and time-critical vision task. Recent years have seen many shallow tracking methods based on real-time pixel-based correlation filters, as w…
PixelNN: Example-based Image Synthesis
Aayush Bansal, Yaser Sheikh, Deva Ramanan
We present a simple nearest-neighbor (NN) approach that synthesizes high-frequency photorealistic images from an "incomplete" signal such as a low-resolution image, a surface norma…
Tracking as Online Decision-Making: Learning a Policy from Streaming Videos with Reinforcement Learning
James Steven Supancic, Deva Ramanan
We formulate tracking as an online decision-making process, where a tracking agent must follow an object despite ambiguous image frames and a limited computational budget. Cruciall…
Comparing Apples and Oranges: Off-Road Pedestrian Detection on the NREC Agricultural Person-Detection Dataset
Zachary Pezzementi, Trenton Tabor, Peiyun Hu +5
Person detection from vehicles has made rapid progress recently with the advent of multiple highquality datasets of urban and highway driving, yet no large-scale benchmark is avail…
Need for Speed: A Benchmark for Higher Frame Rate Object Tracking
Hamed Kiani Galoogahi, Ashton Fagg, Chen Huang +2
In this paper, we propose the first higher frame rate video dataset (called Need for Speed - NfS) and benchmark for visual object tracking. The dataset consists of 100 videos (380K…