1 results about "Random logic" patented technology

This invention discloses a scene graph generation method based on mutual perspective inverse relation calibration and hypernym guidance prompts. First, it establishes the principle of mutual perspective inverse relations and utilizes an adaptive inverse relation enhancement strategy. Through two paths—logical sample expansion and random logical permutation—the inverse perspective logic is internalized into the training process. For large-scale visual language models, hypernym guidance prompts are introduced, abstracting fine-grained entities into a coarse-grained set of hypernyms. This adaptively constructs text features containing inverse logic in the latent space, making the generated representations more consistent with the invariance of mutual perspectives. Finally, the cross-modal mutual perspective representations are jointly optimized using a cross-entropy objective function, serving as the final model prediction parameters. This invention significantly improves the inference robustness of scene graph generation models when facing long-tailed distributed data and complex interactive scenarios, effectively solving the problems of inaccurate identification of rare relations and semantic ambiguity caused by perspective switching.