# Exploring Person Context and Local Scene Context for Object Detection

Source: [Exploring Person Context and Local Scene Context for Object Detection](<https://www.sota2.com/research/paper/68fa62301e209131ce9f80c3>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T20:14:30.423Z

Authors: Saurabh Gupta, Bharath Hariharan, Jitendra Malik

Published: 2015-11-25T19:45:03.000Z

## Abstract

In this paper we explore two ways of using context for object detection. The first model focusses on people and the objects they commonly interact with, such as fashion and sports accessories. The second model considers more general object detection and uses the spatial relationships between objects and between objects and scenes. Our models are able to capture precise spatial relationships between the context and the object of interest, and make effective use of the appearance of the contextual region. On the newly released COCO dataset, our models provide relative improvements of up to 5% over CNN-based state-of-the-art detectors, with the gains concentrated on hard cases such as small objects (10% relative improvement).

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1511.08177>)

[PDF](<https://arxiv.org/pdf/1511.08177.pdf>)