In the last decades, there has been a growing interest in crossmodal correspondences, including those involving temperature. However, only a few studies have explicitly examined the underlying mechanisms behind temperature-related correspondences. Here, we investigated the relative roles of an underlying affective mechanism and a semantic path (i.e., regarding the semantic knowledge related to a single common source identity or meaning) in crossmodal associations between visual textures and temperature concepts using an associative learning paradigm. Two online experiments using visual textures previously shown to be associated with low and high thermal effusivity (Experiment 1) and visual textures with no consensual associations with thermal effusivity (Experiment 2) were conducted. Participants completed a speeded categorisation task before and after an associative learning task, in which they learned mappings between the visual textures and specific affective or semantic stimuli related to low and high temperatures. Across the two experiments, both the affective and semantic mappings influenced the categorisation of visual textures with the hypothesized temperatures, but there was no influence on the reaction times. The effect of learning semantic mappings was larger than that of affective ones in both experiments, suggesting that a semantic path has more weight than an affective mechanism in the formation of the associations studied here. The associations studied here could be modified through associative learning establishing correlations between visual textures and either affective or semantic stimuli.