Early Structural Experience Shapes Visual Representation Learning

During development, infants initially experience a visually degraded world, with limited spatial acuity, contrast sensitivity, chromatic sensitivity, and binocular depth perception that gradually mature over the first months of life. This developmental trajectory may bias early learning toward more stable structural cues, such as boundaries and shape, before richer appearance cues become available. Early-learned structural representations could subsequently serve as attractors that guide the interpretation of richer visual experiences, consistent with infants’ and children’s preference for line drawings and cartoons. Here, we investigate this developmental hypothesis in deep neural networks by using semantically meaningful line drawings as a surrogate of early structural visual experience. Line drawings preserve object boundaries, global shape, and part configurations while suppressing much of the texture and color information present in photographs. We find that early exposure to line drawings systematically reshapes subsequent learning from photographs toward more shape-centered representations. These representational changes improve performance on tasks requiring geometric and spatial understanding, including segmentation and depth estimation, in addition to enhancing recognition, detection, data efficiency, and knowledge distillation. Our findings suggest that early learning based on stable structural information creates a representational foundation to guide the learning of richer visual knowledge in later experience.