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I am working on semantic segmentation using deep learning, and I have met the terms: semantic segmentation, instance detection, object detection and object segmentation.

What is the differences between them?

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guoqiang Wei
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1 Answers1

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Some of the usage of these terms is either subjective to the user or context-dependent, but as far as I can tell a plausible reading of these can be:

instance detection - given an instance (i.e. an image of a specific object) you need to detect it in an image / image set. Result can be either "Image i has instance X", a segmentation of the instance in all of its occurrences or anything in between.

object detection - depending on context can be the same as instance detection, or could mean that given a specific class of objects you want to detect all objects of this class that occur in an image / image set

object segmentation - take object detection and add segmentation of the object in the images it occurs in.

semantic segmentation - attempt to segment given image(s) into semantically interesting parts. This usually means pixel-labeling to a predefined class list.

Another question about image segmentation terminology can be found here and might be of some interest for you.

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ginge
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    I prefer to say that instance detection is to detect different instances of one object in the image, e.g. different people, different cars. Object detection is to detect people and cars, not distinguish instances. I think the terms they use may be different and not conventional. – LI Xuhong Mar 08 '17 at 00:05
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    @Seven - I originally encountered the use of "instance" in the context of computer vision in relation to "instance retrieval" which means finding a specific instance (A specific toy from different and partial view points is a very common example) in an image(s). But all of this terminology is in my experience pretty murky. In the link I gave someone even defines what you describe in your comment as "instance segmentation". – ginge Mar 08 '17 at 13:23