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Instance Search

Visual Instance Search is the task of retrieving from a database of images the ones that contain an instance of a visual query. It is typically much more challenging than finding images from the database that contain objects belonging to the same category as the object in the query. If the visual query is an image of a shoe, visual Instance Search does not try to find images of shoes, which might differ from the query in shape, color or size, but tries to find images of the exact same shoe as the one in the query image. Visual Instance Search challenges image representations as the features extracted from the images must enable such fine-grained recognition despite variations in viewpoints, scale, position, illumination, etc. Whereas holistic image representations, where each image is mapped to a single high-dimensional vector, are sufficient for coarse-grained similarity retrieval, local features are needed for instance retrieval.

Source: Dynamicity and Durability in Scalable Visual Instance Search

Papers

Showing 1120 of 29 papers

TitleStatusHype
Deep Learning for Instance Retrieval: A Survey0
TRECVID 2019: An Evaluation Campaign to Benchmark Video Activity Detection, Video Captioning and Matching, and Video Search & Retrieval0
Deeply Activated Salient Region for Instance Search0
GlobalTrack: A Simple and Strong Baseline for Long-term TrackingCode0
Instance Search via Instance Level Segmentation and Feature Representation0
Saliency Weighted Convolutional Features for Instance SearchCode0
Compressive Quantization for Fast Object Instance Search in Videos0
Learning Non-Metric Visual Similarity for Image Retrieval0
An evaluation of large-scale methods for image instance and class discovery0
Class-Weighted Convolutional Features for Visual Instance SearchCode0
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