Accelerate post-training of end-to-end autonomous vehicle stacks with vector search and retrieval for large video datasets.
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.
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
Ingest massive volumes of live or archived videos and extract insights for summarization and interactive Q&A
Estimate gaze angles of a person in a video and redirect to make it frontal.
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.
