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Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization.

, , , , , , and . ICLR, OpenReview.net, (2021)

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Exemplary Natural Images Explain CNN Activations Better than Feature Visualizations., , , , , , and . CoRR, (2020)How Well do Feature Visualizations Support Causal Understanding of CNN Activations?, , , , , and . NeurIPS, page 11730-11744. (2021)Understanding Low- and High-Level Contributions to Fixation Prediction., , , and . ICCV, page 4799-4808. IEEE Computer Society, (2017)Saliency Benchmarking Made Easy: Separating Models, Maps and Metrics., , and . ECCV (16), volume 11220 of Lecture Notes in Computer Science, page 798-814. Springer, (2018)Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization., , , , , , and . ICLR, OpenReview.net, (2021)The Notorious Difficulty of Comparing Human and Machine Perception., , , , , and . CoRR, (2020)Guiding human gaze with convolutional neural networks., , , and . CoRR, (2017)DeepGaze II: Reading fixations from deep features trained on object recognition., , and . CoRR, (2016)Saliency Benchmarking: Separating Models, Maps and Metrics., , and . CoRR, (2017)Measuring the Importance of Temporal Features in Video Saliency., , , and . ECCV (28), volume 12373 of Lecture Notes in Computer Science, page 667-684. Springer, (2020)