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SAM 3 and SAM 3.1: Video Object Segmentation for Asset Organization and Post-Production

Meta’s SAM 3 series can find, segment and track objects in images or videos based on prompts, and SAM 3.1 further updates multi-target video processing. This article starts from the post-production material preparation of commercial short films, discusses occlusion, edges, object consistency and export checks, explains how the segmentation model participates in production, and why it is not equivalent to automatically generating a complete advertising film.

Chinese edition published 23 Oct 2026 · 阅读中文原文 ↗

Source timingVerified version: SAM 3 official warehouse and SAM 3.1 update; SAM 3.1 release record is March 27, 2026; data verification is on October 23, 2026.

What does segmentation and tracking output?

Meta's official SAM 3 repository introduces the ability to detect, segment, and track objects in images and videos through text and visual cues. The SAM 3.1 update on March 27, 2026 involves multi-target video tracking and provides corresponding weights and code usage requirements.

The segmentation results can be masked to represent the area where the object is located for subsequent processing. This is a different task than generating a new image or automatically cutting it into a full movie. Just because the model can find the object does not mean that the color correction, sound, editing rhythm, and final expression required by the client have been completed.

The product video first defines what to retain (ChinaOPC analysis)

Assuming that the customer provides a set of licensed product clips, you can first clarify the objects that need to be separated, the lenses used, and the final resolution. After testing with a small number of representative clips, decide which materials are suitable for automatic processing and which require manual repair, to avoid discovering that key shots cannot be used after all the materials have been run.

Transparent materials, reflections, rapid motion and overlap of similar objects all deserve separate inspection. The acceptance should not only look at the outline of a certain frame, but also play it continuously to observe whether the edges flicker, disappear briefly, or follow the wrong object. For multiple similar products in the film, it is necessary to confirm that the object number and the actual product always correspond.

Leave an entrance for manual patching

The production process should preserve the original footage, model output, and revised versions. When modifying the mask, record the corresponding shot and time range to facilitate subsequent adjustments or withdrawals; do not directly overwrite the original material as the processing result, otherwise it will be difficult to roll back when the customer changes their needs.

Export also needs to check the size, frame rate, transparency channel or mask file format, and whether the software used by the customer can read it correctly. The separate segmentation results can only be regarded as intermediate products. Only when they enter the customer's actual later process and are used correctly can the agreed delivery be completed.

Acquire models and use materials to confirm separately

The official warehouse explains that there are application and certification steps for weighted access. Before deployment, you should confirm the usage conditions according to the current requirements and match the corresponding code version. Obtaining the model file does not mean that you have the right to use the pictures, characters or brand content in the material. These still need to be processed in conjunction with the scope of authorization provided by the customer.

This article did not run model tests, nor did it measure production efficiency. Small teams can limit the scope of services to material preparation and reviewable post-processing, evaluate costs based on difficult shots and manual corrections, and then decide whether to expand to full content production.

Further reading

Understand video generation and editing; Compare graphic and text data retrieval. For more introduction, please see AI Model Column.

Sources and editorial notes

AI-assisted organizing and writing. The model information is based on the official information at the end of the article; the application process, task examples and acceptance suggestions are original analyzes by ChinaOPC. The model performance evaluation has not been run, and the hypothetical project has not been written as a delivered case. English translation of the Chinese edition, prepared with machine assistance and editorial checks. Source verification dates refer to the original Chinese research.

Source titles and publisher names are retained in their original language. Refer to the linked originals for official documents and current requirements.

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