Studies of spatial visual statistical learning (SVSL) typically focus on the implicit acquisition of co-occurrence-based element chunks oversimplifying the complex process of structure-based visual learning. We investigated the rules of SVSL under complex visual stimulus and task structures. In Phase 1 of the experiment (N=227), observers were exposed to scenes composed of either only horizontally or vertically arranged pairs of shapes, while in Phase 2, they saw scenes based on both horizontal and vertical pairs but using a new set of shapes. 2AFC tests measured observers’ pair-learning for both phases and open questions assessed the explicitness of their knowledge. Participants with complete explicit knowledge were excluded (N=3), while the others were grouped into implicit (N=192) and semi-explicit (N=35) groups based on their reported knowledge about pairs in Phase 1 being none or rudimentary without mentioning orientation. Learning in Phase 2 showed a strong double dissociation between the types of pairs learned preferentially and implicitness of knowledge. Observers with semi-explicit knowledge exceeded learning pairs in Phase 2 with the same orientation as in Phase 1, whereas implicit observers were better at learning pairs with non-matching orientation. Further analyses showed that this pattern was independent of the overall strength of pair learning in Phase 1, but critically depended on the implicitness/explicitness of knowledge. These results suggest that the strength of learning a higher-level structure of the input (here general orientation of pairs) has a crucial role in utilizing the acquired structural knowledge. As expected, when it is sufficiently strongly articulated, it helps generalization, i.e. learning similar patterns in a new context. In contrast, when it is weakly and implicitly captured -regardless of the overall efficiency- it hinders generalization and promotes a structural novelty effect.