Counterfactual Visual Explanations Yash Goyal Ziyan Wu Jan Ernst - - PowerPoint PPT Presentation

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Counterfactual Visual Explanations Yash Goyal Ziyan Wu Jan Ernst - - PowerPoint PPT Presentation

Counterfactual Visual Explanations Yash Goyal Ziyan Wu Jan Ernst Dhruv Batra Devi Parikh Stefan Lee (Georgia Tech) (Siemens) (Siemens) (Georgia Tech) (Georgia Tech) (Georgia Tech) Counterfactual Visual Explanations A Eared Grebe


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SLIDE 1

Counterfactual Visual Explanations

Dhruv Batra (Georgia Tech) Devi Parikh (Georgia Tech) Yash Goyal (Georgia Tech) Jan Ernst (Siemens) Ziyan Wu (Siemens) Stefan Lee (Georgia Tech)

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SLIDE 2

An XAI Question: Why did the model predict Eared Grebe instead of Horned Grebe?

Counterfactual Visual Explanations

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Eared Grebe Horned Grebe Western Grebe Pied-Bill Grebe Herring Gull

Bird Classification Deep Network

A

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SLIDE 3

An XAI Question: Why did the model predict Eared Grebe instead of Horned Grebe?

Counterfactual Visual Explanations

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Eared Grebe Horned Grebe Western Grebe Pied-Bill Grebe Herring Gull

Bird Classification Deep Network

A For input X, why did the model predict Y instead of Z?

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SLIDE 4

An XAI Question: Why did the model predict Eared Grebe instead of Horned Grebe?

Counterfactual Visual Explanations

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Eared Grebe Horned Grebe Western Grebe Pied-Bill Grebe Herring Gull

Bird Classification Deep Network

A Explanation through Counterfactual: If X was X*, then the outcome would have been Z rather than Y. For input X, why did the model predict Y instead of Z?

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SLIDE 5

An XAI Question: Why did the model predict Eared Grebe instead of Horned Grebe?

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Eared Grebe Horned Grebe Western Grebe Pied-Bill Grebe Herring Gull

Bird Classification Deep Network

Explanation through Counterfactual: What would have to change in image A to make the model predict Horned Grebe? A

Counterfactual Visual Explanations

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SLIDE 6

An XAI Question: Why did the model predict Eared Grebe instead of Horned Grebe?

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Eared Grebe Horned Grebe Western Grebe Pied-Bill Grebe Herring Gull

Bird Classification Deep Network

A B

Counterfactual Visual Explanations

An image where the network predicts Horned Grebe.

Explanation through Counterfactual: What would have to change in image A to make the model predict Horned Grebe?

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SLIDE 7

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What would have to change in image A to make the model predict Horned Grebe? A B

An image where the network predicts Horned Grebe.

Counterfactual Visual Explanations

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SLIDE 8

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What would have to change in image A to make the model predict Horned Grebe? A B

An image where the network predicts Horned Grebe.

If looked more like

Counterfactual Visual Explanations

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SLIDE 9

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What would have to change in image A to make the model predict Horned Grebe? A B

An image where the network predicts Horned Grebe.

If looked more like If looked more like

Counterfactual Visual Explanations

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SLIDE 10

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What would have to change in image A to make the model predict Horned Grebe? A B

An image where the network predicts Horned Grebe.

If looked more like If looked more like How can we identify these region pairs important to the model?

Counterfactual Visual Explanations

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SLIDE 11

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Bird Classification Deep Network

How can we identify these region pairs important to the model?

Counterfactual Visual Explanations

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SLIDE 12

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… ℎ𝑥 𝑒 ℎ 𝑒 𝑥 𝑔(𝐽)

Spatial Features

Spatial Feature Extractor

Bird Classification Deep Network

How can we identify these region pairs important to the model?

Counterfactual Visual Explanations

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SLIDE 13

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𝑕(𝑔 𝐽 )

log 𝑄 𝑧. 𝐽) log 𝑄 𝑧/ 𝐽) ⋮ ⋮ log 𝑄(𝑧 1 |𝐽)

… ℎ𝑥 𝑒 ℎ 𝑒 𝑥 𝑔(𝐽)

Spatial Features

Spatial Feature Extractor Decision Network

How can we identify these region pairs important to the model?

Counterfactual Visual Explanations

Bird Classification Deep Network

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SLIDE 14

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𝑔(𝐽3)

Query Image Features

𝑔(𝐽4)

Distractor Image Features

A B

Bird Classification Deep Network

Counterfactual Visual Explanations

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SLIDE 15

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𝑔(𝐽3)

Query Image Features

𝑔(𝐽4)

Distractor Image Features

… … … … … … … … … … … …

𝑄

Permutation Matrix

A B

* dramatization – permutation is in feature space.

Bird Classification Deep Network

Counterfactual Visual Explanations

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SLIDE 16

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𝑔(𝐽3)

Query Image Features

𝑔(𝐽4)

Distractor Image Features

… … … … … … … … … … … …

𝑄

Permutation Matrix

A

Bird Classification Deep Network

1 − 𝑏

Inverted Gating Vector

𝑏

Gating Vector

B

* dramatization – permutation is in feature space.

Counterfactual Visual Explanations

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SLIDE 17

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𝑔(𝐽3)

Query Image Features

𝑔(𝐽4)

Distractor Image Features

… … … … … … … … … … … …

𝑄

Permutation Matrix

A

Bird Classification Deep Network

1 − 𝑏

Inverted Gating Vector

𝑏

Gating Vector

𝑔(𝐽∗)

Counterfactual Edit Image Features

B

* dramatization – permutation is in feature space.

Counterfactual Visual Explanations

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SLIDE 18

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𝑔(𝐽3)

Query Image Features

𝑔(𝐽4)

Distractor Image Features

… … … … … … … … … … … …

𝑄

Permutation Matrix

A

Bird Classification Deep Network

1 − 𝑏

Inverted Gating Vector

𝑏

Gating Vector

𝑔(𝐽∗)

Counterfactual Edit Image Features

* dramatization – replacement is in feature space.

B

* dramatization – permutation is in feature space.

Counterfactual Visual Explanations

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SLIDE 19

𝑔(𝐽3)

Query Image Features

𝑔(𝐽4)

Distractor Image Features

… … … … … … … … … … … …

𝑄

Permutation Matrix

A

Bird Classification Deep Network

1 − 𝑏

Inverted Gating Vector

𝑏

Gating Vector

𝑔(𝐽∗)

Counterfactual Edit Image Features

* dramatization – replacement is in feature space.

B

* dramatization – permutation is in feature space.

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Counterfactual Visual Explanation Generation: Find 1) binary gating vector 𝒃, and 2) a permutation matrix 𝑄

Counterfactual Visual Explanations

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SLIDE 20

𝑔(𝐽3)

Query Image Features

𝑔(𝐽4)

Distractor Image Features

… … … … … … … … … … … …

𝑄

Permutation Matrix

A

Bird Classification Deep Network

1 − 𝑏

Inverted Gating Vector

𝑏

Gating Vector

𝑔(𝐽∗)

Counterfactual Edit Image Features

* dramatization – replacement is in feature space.

B

* dramatization – permutation is in feature space.

20

Counterfactual Visual Explanation Generation: Find 1) binary gating vector 𝒃, and 2) a permutation matrix 𝑄 such that the model changes its decision to the distractor class

Counterfactual Visual Explanations

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SLIDE 21

𝑔(𝐽3)

Query Image Features

𝑔(𝐽4)

Distractor Image Features

… … … … … … … … … … … …

𝑄

Permutation Matrix

A

Bird Classification Deep Network

1 − 𝑏

Inverted Gating Vector

𝑏

Gating Vector

𝑔(𝐽∗)

Counterfactual Edit Image Features

* dramatization – replacement is in feature space.

B

* dramatization – permutation is in feature space.

21

Counterfactual Visual Explanation Generation: Find 1) binary gating vector 𝒃, and 2) a permutation matrix 𝑄 such that the model changes its decision to the distractor class with the fewest edits (i.e. 𝒏𝒋𝒐 𝒃 𝟐)

Counterfactual Visual Explanations

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SLIDE 22

Results – Single Edit

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Eared Grebe Horned Grebe

Query Image A Distractor Image B Composite Image (for visualization only)

If the highlighted region in image A looked like the highlighted region in image B, then image A is more likely to be classified as class B.

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SLIDE 23

Results – Single Edit

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Eared Grebe Horned Grebe

Query Image A Distractor Image B Composite Image (for visualization only)

If the highlighted region in image A looked like the highlighted region in image B, then image A is more likely to be classified as class B.

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SLIDE 24

Results – Single Edit

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Query Image A Distractor Image B Composite Image (for visualization only)

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SLIDE 25

Results – Single Edit

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Query Image A Distractor Image B Composite Image (for visualization only)

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SLIDE 26

Eared Grebe Horned Grebe Olive sided Flycatcher Myrtle Warbler Blue Grosbeak Indigo Bunting

Results – Single Edit

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Query Image A Distractor Image B Composite Image (for visualization only)

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SLIDE 27

Machine Teaching – Bird Classification

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Do our counterfactual explanations help untrained participants learn to identify fine-grained classes?

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SLIDE 28

Machine Teaching – Bird Classification

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Training

Feedback: Sorry, its not a Bravo. It is actually an Alpha.

Do our counterfactual explanations help untrained participants learn to identify fine-grained classes?

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SLIDE 29

Machine Teaching – Bird Classification

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Testing Training

Feedback: Sorry, its not a Bravo. It is actually an Alpha.

Do our counterfactual explanations help untrained participants learn to identify fine-grained classes?

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SLIDE 30

Machine Teaching – Bird Classification

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Do our counterfactual explanations help untrained participants learn to identify fine-grained classes?

71.09 74.29 78.77

50 55 60 65 70 75 80 85 Instant Feedback (IF) IF + Feature Attribution Explanation (GradCAM) IF + Counterfactual Explanation

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SLIDE 31

Questions?

Stop by our poster at #149 in Pacific Ballroom! Eared Grebe Horned Grebe

Query Image A Distractor Image B Composite Image (for visualization only)

Counterfactual Visual Explanations