Abstract: Techniques are generally described for controllable image-to-video generation. In various examples, a first image representing at least a first object may be received. First input data including a selection of the first object in the first image for animation may be received. Second input data including at least a first bounding box indicating a target location of the first object may be received. A latent diffusion text-to-image model and the first image may be used to generate a first plurality of visual tokens. One or more first grounding tokens may be generated representing a location of the first bounding box. The latent diffusion text-to-image model may be used to generate a video animating the first object based on the first plurality of visual tokens and the one or more first grounding tokens.

Abstract: Described herein is a system for tracking objects and performing dynamic entity resolution using image data. For example, the system may build an environment map and populate the map with objects present in the environment. As the devices move about the environment it may capture image data and, based on its position and/or configuration of its components, may determine updated locations of objects that move in the environment. Upon receiving a query from a user, based on the location of the objects relative to the device/user, the system can interpret gestures and voice commands to infer which object is specified by the voice command. To build the environment map, the system performs object detection to generate bounding boxes associated with an object, then clusters the bounding boxes into a three-dimensional (3D) object associated with 3D coordinates. As the system tracks the object using the 3D coordinates while maintaining two-dimensional (2D) information (e.g.

Abstract: Described herein is a system for tracking objects and performing dynamic entity resolution using image data. For example, the system may build an environment map and populate the map with objects present in the environment. As the devices move about the environment it may capture image data and, based on its position and/or configuration of its components, may determine updated locations of objects that move in the environment. Upon receiving a query from a user, based on the location of the objects relative to the device/user, the system can interpret gestures and voice commands to infer which object is specified by the voice command. To build the environment map, the system performs object detection to generate bounding boxes associated with an object, then clusters the bounding boxes into a three-dimensional (3D) object associated with 3D coordinates. As the system tracks the object using the 3D coordinates while maintaining two-dimensional (2D) information (e.g.