Author summary What is the role played by sensory cortices in assessing the emotional significance of sensory input? This question is attracting increasing research interest. Recent work has found affect-specific neural representations in visual cortex. The origins of these representations are debated. According to the reentry hypothesis, these representations result from reentrant feedback arising from anterior emotion processing structures such as the amygdala. An alternative hypothesis holds that sensory cortex may have the intrinsic capacity to represent the emotional qualities of sensory input. We examined this problem by utilizing the convolutional neural networks (CNNs) trained to recognized visual objects as computational models of the primate ventral visual system. Emotionally charged images were divided into three broad categories (pleasant, neutral and unpleasant) and presented to the CNNs. Responses of artificial neurons to these images were found to exhibit robust emotion selectivity. Importantly, enhancing the neurons that were selective for a given emotion led to the increased ability in recognizing that emotion, whereas lesioning these neurons led to the decrease in that ability. This research lends support to the notion that emotional perception might be an intrinsic property of the visual cortex. It also underscores the CNNs’ value in examining neuroscientific theories.