VERIA: Verification-Centric Multimodal Instance Augmentation for Long-Tailed 3D Object Detection

ArXi:2603.24294v1 Announce Type: new Long-tail distributions in driving datasets pose a fundamental challenge for 3D perception, as rare classes exhibit substantial intra-class diversity yet available samples cover this variation space only sparsely. Existing instance augmentation methods based on copy-paste or asset libraries improve rare-class exposure but are often limited in fine-grained diversity and scene-context placement.