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Chanakya: Learning Runtime Decisions for Adaptive Real-Time Perception
v1v2v3 (latest)

Chanakya: Learning Runtime Decisions for Adaptive Real-Time Perception

10 June 2021
Anurag Ghosh
Vaibhav Balloli
A. Nambi
Aditya Singh
T. Ganu
ArXiv (abs)PDFHTML

Papers citing "Chanakya: Learning Runtime Decisions for Adaptive Real-Time Perception"

18 / 18 papers shown
Title
Learned Two-Plane Perspective Prior based Image Resampling for Efficient
  Object Detection
Learned Two-Plane Perspective Prior based Image Resampling for Efficient Object Detection
Anurag Ghosh
Dinesh Reddy Narapureddy
Christoph Mertz
S. Narasimhan
74
4
0
25 Mar 2023
Real-time Object Detection for Streaming Perception
Real-time Object Detection for Streaming Perception
Jinrong Yang
Songtao Liu
Zeming Li
Xiaoping Li
Jian Sun
87
51
0
23 Mar 2022
LegoDNN: Block-grained Scaling of Deep Neural Networks for Mobile Vision
LegoDNN: Block-grained Scaling of Deep Neural Networks for Mobile Vision
Rui Han
Qinglong Zhang
C. Liu
Guoren Wang
Jian Tang
L. Chen
55
44
0
18 Dec 2021
FOVEA: Foveated Image Magnification for Autonomous Navigation
FOVEA: Foveated Image Magnification for Autonomous Navigation
Chittesh Thavamani
Mengtian Li
N. Cebron
Deva Ramanan
61
32
0
27 Aug 2021
Scaled-YOLOv4: Scaling Cross Stage Partial Network
Scaled-YOLOv4: Scaling Cross Stage Partial Network
Chien-Yao Wang
Alexey Bochkovskiy
H. Liao
ObjD
63
1,148
0
16 Nov 2020
ApproxDet: Content and Contention-Aware Approximate Object Detection for
  Mobiles
ApproxDet: Content and Contention-Aware Approximate Object Detection for Mobiles
Ran Xu
Chen-Da Liu-Zhang
Pengcheng Wang
Jayoung Lee
Subrata Mitra
Somali Chaterji
Yin Li
S. Bagchi
54
59
0
21 Oct 2020
TIDE: A General Toolbox for Identifying Object Detection Errors
TIDE: A General Toolbox for Identifying Object Detection Errors
Daniel Bolya
Sean Foley
James Hays
Judy Hoffman
81
195
0
18 Aug 2020
Argoverse: 3D Tracking and Forecasting with Rich Maps
Argoverse: 3D Tracking and Forecasting with Rich Maps
Ming-Fang Chang
John Lambert
Patsorn Sangkloy
Jagjeet Singh
Sławomir Bąk
...
De Wang
Peter Carr
Simon Lucey
Deva Ramanan
James Hays
3DPC
149
1,298
0
06 Nov 2019
MMDetection: Open MMLab Detection Toolbox and Benchmark
MMDetection: Open MMLab Detection Toolbox and Benchmark
Kai-xiang Chen
Jiaqi Wang
Jiangmiao Pang
Yuhang Cao
Yu Xiong
...
Jingdong Wang
Jianping Shi
Wanli Ouyang
Chen Change Loy
Dahua Lin
VOS
175
2,878
0
17 Jun 2019
Searching for MobileNetV3
Searching for MobileNetV3
Andrew G. Howard
Mark Sandler
Grace Chu
Liang-Chieh Chen
Bo Chen
...
Yukun Zhu
Ruoming Pang
Vijay Vasudevan
Quoc V. Le
Hartwig Adam
359
6,804
0
06 May 2019
Tracking without bells and whistles
Tracking without bells and whistles
Philipp Bergmann
Tim Meinhardt
Laura Leal-Taixe
VOT
118
911
0
13 Mar 2019
AdaScale: Towards Real-time Video Object Detection Using Adaptive
  Scaling
AdaScale: Towards Real-time Video Object Detection Using Adaptive Scaling
Ting-Wu Chin
Ruizhou Ding
Diana Marculescu
43
85
0
08 Feb 2019
Hybrid Task Cascade for Instance Segmentation
Hybrid Task Cascade for Instance Segmentation
Kai-xiang Chen
Jiangmiao Pang
Jiaqi Wang
Yu Xiong
Xiaoxiao Li
...
Ziwei Liu
Jianping Shi
Wanli Ouyang
Chen Change Loy
Dahua Lin
ISeg
140
1,307
0
22 Jan 2019
Reactive Reinforcement Learning in Asynchronous Environments
Reactive Reinforcement Learning in Asynchronous Environments
Jaden B. Travnik
K. Mathewson
R. Sutton
P. Pilarski
43
31
0
16 Feb 2018
Action Branching Architectures for Deep Reinforcement Learning
Action Branching Architectures for Deep Reinforcement Learning
Arash Tavakoli
Fabio Pardo
Petar Kormushev
53
264
0
24 Nov 2017
Focal Loss for Dense Object Detection
Focal Loss for Dense Object Detection
Nayeon Lee
Priya Goyal
Ross B. Girshick
Kaiming He
Piotr Dollár
ObjD
127
2,998
0
07 Aug 2017
Speed/accuracy trade-offs for modern convolutional object detectors
Speed/accuracy trade-offs for modern convolutional object detectors
Jonathan Huang
V. Rathod
Chen Sun
Menglong Zhu
Anoop Korattikara Balan
...
Ian S. Fischer
Z. Wojna
Yang Song
S. Guadarrama
Kevin Patrick Murphy
3DH3DV
102
2,572
0
30 Nov 2016
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained
  Quantization and Huffman Coding
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
Song Han
Huizi Mao
W. Dally
3DGS
263
8,859
0
01 Oct 2015
1