LingBot-Vision: masked boundary modeling for self-supervised pretraining (0.296 NYUv2 linear-probe RMSE at 1.1B vs 0.309 for DINOv3-7B, trails on ImageNet); weights in 4 sizes[R]
Summary
LingBot-Vision introduces masked boundary modeling for self-supervised pretraining, achieving a 0.296 RMSE on NYUv2 linear-probe with 1.1B parameters versus 0.309 for DINOv3-7B, though it trails on ImageNet; weights are released in four sizes.
Similar Articles
Ant Group released LingBot-Vision: DINO-family vision backbones in 4 sizes, and the 0.3B ViT-L matches DINOv3-7B on NYUv2 depth with ~23x fewer params
Ant Group released LingBot-Vision, a family of DINO-style vision backbones in 4 sizes; the 0.3B ViT-L matches DINOv3-7B on NYUv2 depth with ~23x fewer parameters, showcasing significant efficiency gains.
@rohanpaul_ai: A 1B-parameter vision model just beat a 7B one on depth, frozen, single linear layer, zero fine-tuning. @robbyant_brain…
Robbyant releases LingBot-Vision, a 1B-parameter vision model trained on boundaries that achieves better depth estimation than DINOv3-7B, with open weights.
@AdinaYakup: LingBot Vision A self-supervised vision backbone family for dense spatial perception from Ant Group @robbyant_brain - A…
LingBot Vision, a self-supervised vision backbone family from Ant Group, uses masked boundary modeling to achieve state-of-the-art performance on dense spatial perception tasks, beating the larger DINOv3 model on NYU-Depth v2.
Vision Pretraining for Dense Spatial Perception
This paper introduces masked boundary modeling, a self-supervised paradigm for vision pretraining that learns sub-pixel boundary representations to improve dense spatial perception. The resulting model, LingBot-Vision, demonstrates significant improvements in depth estimation and other downstream tasks, showing that boundary modeling is a scalable pretraining principle for spatially structured visual representations.
@AdinaYakup: Powered by the new LingBot Vision https://huggingface.co/collections/robbyant/lingbot-vision… - Apache 2.0 - 4 versions…
LingBot Vision is a new visual foundation model released under Apache 2.0, available in four sizes (small, base, large, giant) and pretrained with masked boundary modeling. It powers a depth estimation system that tops multiple benchmarks.