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Nov 9, 2023 · Recent research has shown that deep models are vulnerable to images containing adverse weather corruptions, leading to a safety risk for ...
Mar 21, 2024 · 3) Experiments on five benchmark datasets show that our method can enhance state-of-the-art models against dif- ferent weather corruptions. The ...
Recent research has shown that deep models are vulnerable to images containing adverse weather corruptions, leading to a safety risk for numerous safety- ...
May 17, 2023 · We use 8 drift scenarios, depicted in Table 5, whose ground truth root causes of drifts are different combinations of three weather corruptions ...
Deep Counterfactual Representation Learning for Visual Recognition Against Weather Corruptions · Published: 31 Dec 2023, Last Modified: 06 Oct 2024 · IEEE Trans.
Deep Counterfactual Representation Learning for Visual Recognition Against Weather Corruptions. IEEE Transactions on Multimedia. 2024 | Journal article. DOI ...
221-239, Cambridge University Press, 2024. Deep Counterfactual Representation Learning for Visual Recognition against Weather Corruptions Hong Liu, Yongqing ...
Recent research has shown that deep models are vulnerable to images containing adverse weather corruptions, leading to a safety risk for numerous safety- ...
Deep Counterfactual Representation Learning for Visual Recognition Against Weather Corruptions. IEEE Trans. Multim. Hong Liu 0009; ,; Yongqing Sun; ,; Yukihiro ...
... image corruption. Models generalize well for image noise and image blur, however, not with respect to digitally corrupted data or weather corruptions.