Scene Understanding

Scene understanding involves interpreting the visual information of a scene, including objects, their spatial relationships, and the overall layout. It goes beyond simple object recognition by considering the context and how objects relate to each other and the environment.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1471–1480 of 1723 papers

Title	Date	Tasks	Status	Hype
Software-Defined FPGA Accelerator Design for Mobile Deep Learning Applications	Feb 8, 2019	Deep LearningHigh-Level Synthesis	—Unverified	0
Single Network Panoptic Segmentation for Street Scene Understanding	Feb 7, 2019	Instance SegmentationPanoptic Segmentation	CodeCode Available	0
Real-time 3D Traffic Cone Detection for Autonomous Driving	Feb 6, 2019	3D Object DetectionAutonomous Driving	CodeCode Available	0
VrR-VG: Refocusing Visually-Relevant Relationships	Feb 1, 2019	Image CaptioningQuestion Answering	—Unverified	0
Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detection	Jan 25, 2019	Anomaly DetectionDecoder	CodeCode Available	0
Neural RGB->D Sensing: Depth and Uncertainty from a Video Camera	Jan 9, 2019	3D Reconstruction3D Scene Reconstruction	CodeCode Available	0
Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene Understanding	Jan 5, 2019	Domain AdaptationScene Understanding	CodeCode Available	1
Learning Spatial Common Sense with Geometry-Aware Recurrent Networks	Dec 31, 2018	Common Sense ReasoningRepresentation Learning	—Unverified	0
Impact of Ground Truth Annotation Quality on Performance of Semantic Image Segmentation of Traffic Conditions	Dec 30, 2018	Autonomous DrivingImage Segmentation	CodeCode Available	0
Reasoning About Physical Interactions with Object-Oriented Prediction and Planning	Dec 28, 2018	ObjectScene Understanding	—Unverified	0

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All datasets Semantic Scene Understanding Challenge (passive actuation & ground-truth localisation)ADE20K val Semantic Scene Understanding Challenge (active actuation & ground-truth localisation)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ACRV Baseline	OMQ	0.44	—	Unverified
2	Team VGAI (TCS Research)	OMQ	0.37	—	Unverified
3	Demo_semantic_SLAM	OMQ	0.11	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CPN(ResNet-101)	Mean IoU	46.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ACRV Baseline	OMQ	0.35	—	Unverified