Search Results for author: Vivek Rathod

Found 12 papers, 10 papers with code

The surprising impact of mask-head architecture on novel class segmentation

3 code implementations ICCV 2021 Vighnesh Birodkar, Zhichao Lu, Siyang Li, Vivek Rathod, Jonathan Huang

Under this family, we study Mask R-CNN and discover that instead of its default strategy of training the mask-head with a combination of proposals and groundtruth boxes, training the mask-head with only groundtruth boxes dramatically improves its performance on novel classes.

Instance Segmentation Semantic Segmentation

RetinaTrack: Online Single Stage Joint Detection and Tracking

1 code implementation CVPR 2020 Zhichao Lu, Vivek Rathod, Ronny Votel, Jonathan Huang

Traditionally multi-object tracking and object detection are performed using separate systems with most prior works focusing exclusively on one of these aspects over the other.

Autonomous Driving Multi-Object Tracking +2

Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection

2 code implementations CVPR 2020 Sara Beery, Guanhang Wu, Vivek Rathod, Ronny Votel, Jonathan Huang

In this paper we propose a method that leverages temporal context from the unlabeled frames of a novel camera to improve performance at that camera.

Video Object Detection Video Understanding

Pooling Pyramid Network for Object Detection

2 code implementations9 Jul 2018 Pengchong Jin, Vivek Rathod, Xiangxin Zhu

We share box predictors across all scales, and replace convolution between scales with max pooling.

Object Detection

Semantic Instance Segmentation via Deep Metric Learning

1 code implementation30 Mar 2017 Alireza Fathi, Zbigniew Wojna, Vivek Rathod, Peng Wang, Hyun Oh Song, Sergio Guadarrama, Kevin P. Murphy

We propose a new method for semantic instance segmentation, by first computing how likely two pixels are to belong to the same object, and then by grouping similar pixels together.

Instance Segmentation Metric Learning +2

Deep Metric Learning via Facility Location

1 code implementation CVPR 2017 Hyun Oh Song, Stefanie Jegelka, Vivek Rathod, Kevin Murphy

Learning the representation and the similarity metric in an end-to-end fashion with deep networks have demonstrated outstanding results for clustering and retrieval.

Metric Learning Structured Prediction

Speed/accuracy trade-offs for modern convolutional object detectors

13 code implementations CVPR 2017 Jonathan Huang, Vivek Rathod, Chen Sun, Menglong Zhu, Anoop Korattikara, Alireza Fathi, Ian Fischer, Zbigniew Wojna, Yang song, Sergio Guadarrama, Kevin Murphy

On the opposite end in which accuracy is critical, we present a detector that achieves state-of-the-art performance measured on the COCO detection task.

Ranked #174 on Object Detection on COCO test-dev (using extra training data)

Object Detection

Im2Calories: Towards an Automated Mobile Vision Food Diary

no code implementations ICCV 2015 Austin Meyers, Nick Johnston, Vivek Rathod, Anoop Korattikara, Alex Gorban, Nathan Silberman, Sergio Guadarrama, George Papandreou, Jonathan Huang, Kevin P. Murphy

We present a system which can recognize the contents of your meal from a single image, and then predict its nutritional contents, such as calories.

Bayesian Dark Knowledge

1 code implementation NeurIPS 2015 Anoop Korattikara, Vivek Rathod, Kevin Murphy, Max Welling

We consider the problem of Bayesian parameter estimation for deep neural networks, which is important in problem settings where we may have little data, and/ or where we need accurate posterior predictive densities, e. g., for applications involving bandits or active learning.

Active Learning

What's Cookin'? Interpreting Cooking Videos using Text, Speech and Vision

1 code implementation5 Mar 2015 Jonathan Malmaud, Jonathan Huang, Vivek Rathod, Nick Johnston, Andrew Rabinovich, Kevin Murphy

We present a novel method for aligning a sequence of instructions to a video of someone carrying out a task.

Keyword Spotting

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