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1T multimodal MoE for high‑capacity video and image understanding with efficient inference.
Vision language model that excels in understanding the physical world using structured reasoning on videos or images.
Nemotron Nano 12B v2 VL enables multi-image and video understanding, along with visual Q&A and summarization capabilities.
Reasoning vision language model (VLM) for physical AI and robotics.
Generates physics-aware video world states for physical AI development using text prompts and multiple spatial control inputs derived from real-world data or simulation.
Estimate gaze angles of a person in a video and redirect to make it frontal.
Generates future frames of a physics-aware world state based on simply an image or short video prompt for physical AI development.
Multi-modal vision-language model that understands text/img/video and creates informative responses
Visual Changenet detects pixel-level change maps between two images and outputs a semantic change segmentation mask
EfficientDet-based object detection network to detect 100 specific retail objects from an input video.
