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+*This model was published in HF papers on 2025-04-17 and contributed to Hugging Face Transformers on 2025-07-11.*
+
+# PerceptionLM
+
+## Overview
+
+The [PerceptionLM](https://huggingface.co/papers/2504.13180) model was proposed in [PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding](https://ai.meta.com/research/publications/perceptionlm-open-access-data-and-models-for-detailed-visual-understanding/) by Jang Hyun Cho et al. It's a fully open, reproducible model for transparent research in image and video understanding. PLM consists of
+a vision encoder with a small scale (<8B parameters) LLM decoder.
+
+The abstract from the paper is the following:
+
+*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.*
+
+This model was contributed by [shumingh](https://huggingface.co/shumingh).
+The original code can be found [here](https://github.com/facebookresearch/perception_models).
+
+## PerceptionLMConfig
+
+[[autodoc]] PerceptionLMConfig
+
+## PerceptionLMProcessor
+
+[[autodoc]] PerceptionLMProcessor
+    - __call__
+
+## PerceptionLMImageProcessor
+
+[[autodoc]] PerceptionLMImageProcessor
+    - preprocess
+
+## PerceptionLMVideoProcessor
+
+[[autodoc]] PerceptionLMVideoProcessor
+
+## PerceptionLMModel
+
+[[autodoc]] PerceptionLMModel
+
+## PerceptionLMForConditionalGeneration
+
+[[autodoc]] PerceptionLMForConditionalGeneration
+    - forward