Supplemental Material

To strengthen the design rationale for incorporating prompts instead of following recent methods [3] Table 1: Comparisons under all-in-one setting: between the usage of degradation embedding extracted from the Contrastive-learning Based Degradation Encoder (CBDE) of the Airnet [3] Model and the usage of prompt tokens in the PromptIR framework. We show that it is important the prompt block is only used on the decoder side. Table 2: Comparisons under the all-in-one setting: between the usage of the Prompt-block on both the encoder branch and encoder branch with using the prompt block only on the decoder branch. Figure 1: Overview of the Transformer block used in the PromptIR framework. The Transformer block is composed of two sub modules,the Multi Dconv head transposed attention module(MDTA) and the Gated Dconv feed-forward network(GDFN).