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The Official Repository for "Generalized OOD Detection: A Survey"

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out-of-distribution-detection ood-detection anomaly-detection novelty-detection open-set-recognition outlier-detection

oodsurvey's Introduction

Hi, there! ๐Ÿ‘‹

๐ŸŽ’ I am pursuing my PhD on the topic of visual perception and reasoning in the open world.

๐Ÿ”ญ Iโ€™m recently focusing on scene graph generation ๐Ÿ•ธ, vision language models ๐Ÿง , and embodied AI ๐Ÿค–๏ธ.

oodsurvey's People

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icgy96 avatar jediwarriorzou avatar jingkang50 avatar kingjamessong avatar lilydaytoy avatar lvzongyao avatar omegading avatar prophet-c avatar yixuanli avatar zixusong avatar zzitang avatar

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oodsurvey's Issues

OOD/OSR of mlti-label recognition

Hi.Amazing survey,but i notice for recognition task mlti-label recognition is missed,wonder is there any progress or amazing work for OOD/OSR of mlti-label recognition?

the topic "novety class discovery" is missing.

nice work. I notice that the topic about "novety class discovery" is missing. That is, sometimes it is not enough for the ood samples
are just recognized as class "ood", they also need to be specifically classified. I recommend that the authors could consider to add this part.

Question: I wonder why the "Representation Enhancement" could be categorized as one of the models under the "Density Estimation with Deep Generative Models"?

Hi,

Really thanks for this super comprehensive survey, which really helped me get to the basic level of this area with a complete framework, and saved a lot of my time. I understood most of the paper but still got a few questions. I am curious about this question mostly: I wonder why the "Representation Enhancement" could be categorized as one of the models under the "Density Estimation with Deep Generative Models", what is the reason that leads you to put it as d part under 3.1.2?

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