Segment fusion based robust semantic segmentation of scenes using a graph clusterer
AssigneeIntel Corporation
InventorsAnirud Thyagharajan, Prashant Laddha, Benjamin Ummenhofer, Om Ji Omer
Life of this patent
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Abstract
Systems, apparatuses and methods may provide for technology that identifies a plurality of segments based on semantic features and instance features associated with a scene, fuses the plurality of segments into a plurality of instances, and selects classification labels for the plurality of instances. In one example, the plurality of segments is fused into the plurality of instances via a learnable self-attention based network.
Claims22
A computing system comprising:
- a network controller to obtain data corresponding to a scene;
- a processor coupled to the network controller;
- and
- a memory including a set of instructions, which when executed by the processor, cause the processor to:
- use a first neural network to generate semantic features,
- use a second neural network to generate instance features,
- identify a plurality of segments using a graph clusterer based on the semantic features, the instance features, and point cloud data associated with the scene,
- fuse the plurality of segments into a plurality of instances, wherein the plurality of segments is to be fused into the plurality of instances via a learnable self-attention based network, and
- select classification labels for the plurality of instances.
At least one non-transitory computer readable storage medium comprising a set of instructions, which when executed by a computing system, cause the computing system to:
- use a first neural network to generate semantic features;
- use a second neural network to generate instance features;
- identify a plurality of segments using a graph cluster based on the semantic features, the instance features, and point cloud data associated with a scene;
- fuse the plurality of segments into a plurality of instances, wherein the plurality of segments is to be fused into the plurality of instances via a learnable self-attention based network;
- and
- select classification labels for the plurality of instances.
A semiconductor apparatus comprising:
- one or more substrates;
- and
- logic coupled to the one or more substrates, wherein the logic is implemented at least partly in one or more of configurable or fixed-functionality hardware, the logic to:
- use a first neural network to generate semantic features,
- use a second neural network to generate instance features,
- identify a plurality of segments using a graph clusterer based on the semantic features, the instance features, and point cloud data associated with a scene,
- fuse the plurality of segments into a plurality of instances, wherein the plurality of segments is to be fused into the plurality of instances via a learnable self-attention based network, and
- select classification labels for the plurality of instances.
A method comprising:
- using a first neural network to generate semantic features,
- using a second neural network to generate instance features,
- identifying a plurality of segments using a graph cluster based on the semantic features, the instance features, and point cloud data associated with a scene;
- fusing the plurality of segments into a plurality of instances, wherein the plurality of segments is fused into the plurality of instances via a learnable self-attention based network;
- and
- selecting classification labels for the plurality of instances.
Dependencies are inferred from the claim text.