UniWorld Workshop @ ECCV2026

Computer vision is shifting from task-specific pipelines to general-purpose multimodal foundation models. Yet current systems remain fragmented: perception models recognize, generative models synthesize, and reasoning often occurs mainly in language space. This separation limits scalability, transferability, and holistic scene understanding.

Recent progress in multimodal large models, neural scene representations, video foundation models, and embodied world models suggests these directions are converging. UniWorld targets this moment by promoting universal representations that unify perception, reasoning, generation, and interaction within a coherent framework.

Despite rapid advances, core challenges remain: designing architectures for heterogeneous data, mitigating task interference, enabling compositional reasoning, and achieving robust generalization across domains. By bringing together researchers across foundation models, multimodal learning, and world modeling, UniWorld aims to catalyze principled approaches toward generalizable visual intelligence.