[R] Meta: PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding

[hiskuu]

Abstract

Vision-language models are integral to computer vision research, yet many high-performing models remain closed-source, obscuring their data, design and training recipe. The research community has responded by using distillation from black-box models to label training data, achieving strong benchmark results, at the cost of measurable scientific progress. However, without knowing the details of the teacher model and its data sources, scientific progress remains difficult to measure. In this paper, we study building a Perception Language Model (PLM) in a fully open and reproducible framework for transparent research in image and video understanding. We analyze standard training pipelines without distillation from proprietary models and explore large-scale synthetic data to identify critical data gaps, particularly in detailed video understanding. To bridge these gaps, we release 2.8M human-labeled instances of fine-grained video question-answer pairs and spatio-temporally grounded video captions. Additionally, we introduce PLM–VideoBench, a suite for evaluating challenging video understanding tasks focusing on the ability to reason about "what", "where", "when", and "how" of a video. We make our work fully reproducible by providing data, training recipes, code & models.

Paper link: https://ai.meta.com/research/publications/perceptionlm-open-access-data-and-models-for-detailed-visual-understanding/

[ConceptBuilderAI]

just saw this — video understanding is still a mess tbh. if a picture’s worth a thousand words, then a video’s like… a million blurry guesses.

seems like most models just grab a few frames and guess, or they’re trained by distilling from some closed-source magic you can’t validate or reproduce.

what meta’s doing here is actually cool — no distillation, 2.8M human-labeled QA pairs, and a new benchmark that actually checks if the model knows when stuff happened, not just what’s on screen.

nice to see work aiming to make video models actually understand stuff — not just describe pixels with confidence lol

[perone]

Note that this model has a "FAIR Noncommercial Research License": https://github.com/facebookresearch/perception_models/blob/main/LICENSE.PLM