LingBot-Vision
PulseAugur coverage of LingBot-Vision — every cluster mentioning LingBot-Vision across labs, papers, and developer communities, ranked by signal.
- 2026-07-07 product_launch Ant Group's AI lab has open-sourced LingBot-Vision and LingBot-Depth 2.0, foundational models for embodied AI to improve robot spatial perception. source
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BruNet framework achieves state-of-the-art bruise segmentation
Researchers have developed BruNet, a novel framework for segmenting bruises in medical images, addressing the challenges of limited data and variable appearance. This framework utilizes a ViT-based visual encoder, such …
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Ant Group open-sources LingBot-Vision for robots to better perceive the world
Ant Group's AI lab has open-sourced LingBot-Vision, a foundational vision model designed for embodied AI, and LingBot-Depth 2.0, a spatial perception model built upon it. These models aim to significantly improve how ro…
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LingBot-Vision uses masked boundary modeling for self-supervised pretraining
Researchers have introduced LingBot-Vision, a new self-supervised pretraining method that focuses on masked boundary modeling. This approach aims to improve performance by forcing the model to reconstruct specific bound…
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Ant Group's Lingbo releases suite of embodied AI models, including world action and video generation
Ant Group's Lingbo Technology has released a suite of new models aimed at advancing embodied AI and robotics. LingBot-VA 2.0 is presented as the first embodiment-native world action model, designed from the ground up fo…
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Ant Group subsidiary Lingbo Tech unveils advanced spatial perception model
Lingbo Technology, an embodied intelligence company under Ant Group, has released LingBot-Depth 2.0, a spatial perception model trained on 150 million data points. This new model offers significant upgrades in edge clar…
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New vision pretraining framework enhances dense spatial perception and depth estimation · 3 sources tracked
Researchers have introduced LingBot-Vision, a novel self-supervised pretraining framework focused on boundary modeling for dense spatial perception. This approach enhances depth estimation, a critical component for embo…