SenseTime Open-Sources Visual Multimodal Model
JaynitMakwana · x · 2026-07-13
SenseTime has released and open-sourced SenseNova-Vision-7B-MoT, promoting the concept of "one model covering major vision tasks."
The content highlights that it reformulates traditional computer vision into a multimodal generative system controllable by language or visual prompts, eliminating the need for task-specific heads.
It also provides benchmark comparisons against Google DeepMind Vision Banana, claiming superior performance on multiple tasks, such as:
- RefCOCOg referring expression segmentation: 80.3 vs 73.8
- Cityscapes semantic segmentation: 71.2 vs 69.9
- NYUv2 depth estimation: 98.1 vs 94.8
- NYUv2 normal estimation: 14.4 vs 17.8
The release notes also mention that this is a new generation of visual multimodal model built on SenseTime's decade of experience in vision AI.
Related event: SenseTime open-sources SenseNova-Vision-7B-MoT unified vision model(6 posts)→
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