Scene Segmentation
121 papers with code • 5 benchmarks • 7 datasets
Scene segmentation is the task of splitting a scene into its various object components.
Image adapted from Temporally coherent 4D reconstruction of complex dynamic scenes.
Benchmarks
These leaderboards are used to track progress in Scene Segmentation
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Libraries
Use these libraries to find Scene Segmentation models and implementations
ScanNet
NYUv2
SUN RGB-D
UAVid
StreetHazards
Mila Simulated Floods
Berkeley DeepDrive Video
Latest papers
GNeSF: Generalizable Neural Semantic Fields
hlinchen/gnesf
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NeurIPS 2023
We propose a novel soft voting mechanism to aggregate the 2D semantic information from different views for each 3D point.
Loci-Segmented: Improving Scene Segmentation Learning
CognitiveModeling/Loci-Segmented
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Current slot-oriented approaches for compositional scene segmentation from images and videos rely on provided background information or slot assignments.
APNet: Urban-level Scene Segmentation of Aerial Images and Point Clouds
codename1995/APNet_ICCVW23
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To leverage the different properties of each branch, we employ a geometry-aware fusion module that is learned to combine the results of each branch.
MA-SAM: Modality-agnostic SAM Adaptation for 3D Medical Image Segmentation
cchen-cc/ma-sam
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The Segment Anything Model (SAM), a foundation model for general image segmentation, has demonstrated impressive zero-shot performance across numerous natural image segmentation tasks.
Double Domain Guided Real-Time Low-Light Image Enhancement for Ultra-High-Definition Transportation Surveillance
qujx/ddnet
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Real-time transportation surveillance is an essential part of the intelligent transportation system (ITS).
Self-Supervised Pre-Training Boosts Semantic Scene Segmentation on LiDAR Data
marionacaros/barlow-twins-for-sem-seg
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Airborne LiDAR systems have the capability to capture the Earth's surface by generating extensive point cloud data comprised of points mainly defined by 3D coordinates.
Robotic Scene Segmentation with Memory Network for Runtime Surgical Context Inference
uva-dsa/runtime_robscene_seg_2context
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However, runtime context inference is challenging since it requires timely and accurate detection of the interactions among the tools and objects in the surgical scene based on the segmentation of video data.
AdaptiveSAM: Towards Efficient Tuning of SAM for Surgical Scene Segmentation
However, SAM does not generalize well to the medical domain as is without utilizing a large amount of compute resources for fine-tuning and using task-specific prompts.
Unmasking Anomalies in Road-Scene Segmentation
shyam671/mask2anomaly-unmasking-anomalies-in-road-scene-segmentation
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ICCV 2023
We propose a paradigm change by shifting from a per-pixel classification to a mask classification.
Learning Content-enhanced Mask Transformer for Domain Generalized Urban-Scene Segmentation
BiQiWHU/CMFormer
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Unlike domain gap challenges, USSS is unique in that the semantic categories are often similar in different urban scenes, while the styles can vary significantly due to changes in urban landscapes, weather conditions, lighting, and other factors.
