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WeVisOne-VL

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LLMsComputer Vision ToolsOpen source · Web

WeVisOne-VL is a unified vision-language model developed by WeChat Vision, Tencent Inc. It integrates object-level and pixel-level perception for tasks like object detection and image matting, designed for research purposes.

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WeVisOne-VL screenshot
WeVisOne-VL screenshot

Description

WeVisOne-VL is a sophisticated vision-language model developed by WeChat Vision, a division of Tencent Inc. This model is built upon the Qwen3-VL framework and is designed to unify object-level and pixel-level perception tasks. It is capable of handling open-vocabulary object detection, referring localization, object counting, object pointing, and optical character recognition (OCR). Additionally, it supports pixel-level tasks such as referring segmentation and promptable alpha matting.

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The model employs structured next-token prediction and features a lightweight pixel decoder with 9.5 million parameters. A key component of WeVisOne-VL is the mask_decoder.pt, which integrates a Visual Feature Adapter, a Box-Guided Query Decoder, and an Instance-Conditioned Dense Prediction Head. These components work together to refine predictions and output high-resolution alpha mattes.

WeVisOne-VL is intended for research applications in visual grounding, localization, pointing, counting, OCR, segmentation, and image matting. It is not designed for autonomous decision-making or individual identification. The model is optimized for single-turn image perception and does not support video grids.

The model is released under the Apache License 2.0, with third-party components retaining their original licenses. Users are encouraged to review the source files for specific licensing details.

  • CategoryComputer Vision Tools
  • Pricing ModelOpen source
  • DeploymentCloud
  • PlatformsWeb

WeVisOne-VL Highlights

  • Unified vision-language model

  • Object-level perception

  • Pixel-level perception

  • Open-vocabulary object detection

  • Referring segmentation

  • Promptable alpha matting

  • Structured next-token prediction

  • Lightweight pixel decoder

Getting Started with WeVisOne-VL

  1. Access model page: Visit the Hugging Face model page

  2. Authenticate: Log in to your Hugging Face account

  3. Configure: Set up the model with necessary parameters

  4. Send prompts: Input your visual data for processing

  5. Fine-tune: Adjust model settings for specific tasks

WeVisOne-VL's Use Cases

  • Visual Grounding
  • Object Detection
  • Image Matting
  • OCR Localization
  • Referring Segmentation

FAQ from WeVisOne-VL

From Tencent

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