3 accepted papers
In image denoising research, discriminative models have achieved impressive results which mainly owes to the powerful ability of convolutional networks in local feature extraction. However, there is still room for improvement due to insufficient utilization of global information. Although using full
Recent advances in causal interpretability have extended from language models to vision-language models (VLMs), seeking to reveal their internal mechanisms through input interventions. While textual interventions often target semantics, visual interventions typically rely on coarse pixel-level pertu
Image denoising methods based on convolutional neural networks have been popular and achieved relatively excellent performance. However, most of the existing methods cannot fully obtain and use the shallow feature information when removing noise, and cannot better combine information between various…