Abstract: In one embodiment, a computing system instructs, at a first time, a camera having a plurality of pixel sensors to use the plurality of pixel sensors to capture a first image of an environment comprising an object. The computing system predicts, using at least the first image, a projection of the object appearing in a virtual image plane associated with a predicted camera pose at a second time. The computing system determines, based on the predicted projection of the object, a first region of pixels and a second region of pixels. The computing system generates pixel-activation instructions for the first region of pixels and the second region of pixels. The computing system instructs the camera to capture a second image of the environment at the second time according to the pixel-activation instructions.

Abstract: In one embodiment, a computing system instructs, at a first time, a camera having a plurality of pixel sensors to use the plurality of pixel sensors to capture a first image of an environment comprising an object. The computing system predicts, using at least the first image, a projection of the object appearing in a virtual image plane associated with a predicted camera pose at a second time. The computing system determines, based on the predicted projection of the object, a first region of pixels and a second region of pixels. The computing system generates pixel-activation instructions for the first region of pixels and the second region of pixels. The computing system instructs the camera to capture a second image of the environment at the second time according to the pixel-activation instructions.

Abstract: In one embodiment, a method includes instructing, at a first time, a camera having a plurality of pixel sensors to capture a first image of an environment comprising an object to determine a first object pose; determining, based on the first object pose, a predicted object pose of the object at a second time; generating pixel-activation instructions based on a buffer region around a projection of a 3D model of the object having the predicted object pose onto a virtual image plane associated with a predicted camera pose, where the size of the buffer region may be dependent on predicted dynamics for the object; instructing, at the second time, the camera to use a subset of the plurality of pixel sensors to capture a second image of the environment according to the pixel-activation instructions, and; determining, based on the second image, a second object pose of the object.

Abstract: In one embodiment, a method includes instructing, at a first time, a camera having a plurality of pixel sensors to capture a first image of an environment comprising an object to determine a first object pose; determining, based on the first object pose, a predicted object pose of the object at a second time; generating pixel-activation instructions based on a buffer region around a projection of a 3D model of the object having the predicted object pose onto a virtual image plane associated with a predicted camera pose, where the size of the buffer region may be dependent on predicted dynamics for the object; instructing, at the second time, the camera to use a subset of the plurality of pixel sensors to capture a second image of the environment according to the pixel-activation instructions, and; determining, based on the second image, a second object pose of the object.

Abstract: In one embodiment, a computing system accesses a plurality of images captured by one or more cameras from a plurality of camera poses. The computing system generates, using the plurality of images, a plurality of semantic segmentations comprising semantic information of one or more objects captured in the plurality of images. The computing system accesses a three-dimensional (3D) model of the one or more objects. The computing system determines, using the plurality of camera poses, a corresponding plurality of virtual camera poses relative to the 3D model of the one or more objects. The computing system generates a semantic 3D model by projecting the semantic information of the plurality of semantic segmentations towards the 3D model using the plurality of virtual camera poses.

Abstract: In one embodiment, a method includes instructing, at a first time, a camera with multiple pixel sensors to capture a first image of an environment comprising an object to determine a first object pose of the object. Based on the first object pose, the method determines a predicted object pose of the object at a second time. The method determines a predicted camera pose of the camera at the second time. The method generates pixel-activation instructions based on a projection of a 3D model of the object having the predicted object pose onto a virtual image plane associated with the predicted camera pose. The method instructs, at the second time, the camera to use a subset of the plurality of pixel sensors to capture a second image of the environment according to the pixel-activation instructions. The method determines, based on the second image, a second object pose of the object.

Abstract: In one embodiment, a computing system accesses a plurality of images captured by one or more cameras from a plurality of camera poses. The computing system generates, using the plurality of images, a plurality of semantic segmentations comprising semantic information of one or more objects captured in the plurality of images. The computing system accesses a three-dimensional (3D) model of the one or more objects. The computing system determines, using the plurality of camera poses, a corresponding plurality of virtual camera poses relative to the 3D model of the one or more objects. The computing system generates a semantic 3D model by projecting the semantic information of the plurality of semantic segmentations towards the 3D model using the plurality of virtual camera poses.