2D Semantic Segmentation
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Benchmarks
Deep Indices
WildScenes
xBD
RELLIS-3D
CamVid
Cityscapes val
Extended heartSeg
GF-PA66 3D XCT
WaterScenes
WorldFloods
Most implemented
Rethinking Atrous Convolution for Semantic Image Segmentation
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
Unified Perceptual Parsing for Scene Understanding
Masked-attention Mask Transformer for Universal Image Segmentation
xBD: A Dataset for Assessing Building Damage from Satellite Imagery
Papers
SAM3 Self-Distillation for Fine-Grained GOOSE 2D Semantic Segmentation
We describe our 4th-place entry to the ICRA 2026 GOOSE 2D Fine-Grained Semantic Segmentation Challenge, which reached a composite mean Intersection-over-Union (mIoU) of 69.73% on the official 1,815-image test set. Our mo…
2D Semantic SegmentationUnsOcc: 3D Semantic Occupancy Prediction in Unstructured Scene via Rendering Fusion
Unstructured scenes present unique challenges for autonomous driving, as irregular obstacles and sparse scene layouts undermine the effectiveness of traditional perception methods such as 3D object detection. 3D semantic…
2D Semantic Segmentation3D Object DetectionAutonomous DrivingGeometric Flood Depth Estimation: Fusing Transformer-Based Segmentation with Digital Elevation Models
Post-disaster situational awareness relies heavily on understanding both the extent and the volume of floodwaters. While 2D semantic segmentation provides accurate flood masking, it lacks the vertical dimension required …
2D Semantic SegmentationDepth EstimationCross-Attentive Multiview Fusion of Vision-Language Embeddings
Vision-language models have been key to the development of open-vocabulary 2D semantic segmentation. Lifting these models from 2D images to 3D scenes, however, remains a challenging problem. Existing approaches typically…
2D Semantic SegmentationSpaceSense-Bench: A Large-Scale Multi-Modal Benchmark for Spacecraft Perception and Pose Estimation
Autonomous space operations such as on-orbit servicing and active debris removal demand robust part-level semantic understanding and precise relative navigation of target spacecraft, yet collecting large-scale real data …
Monocular Depth EstimationPoint Cloud Segmentation2D Semantic SegmentationObject DetectionXD-MAP: Cross-Modal Domain Adaptation via Semantic Parametric Maps for Scalable Training Data Generation
Until open-world foundation models match the performance of specialized approaches, deep learning systems remain dependent on task- and sensor-specific data availability. To bridge the gap between available datasets and …
2D Semantic Segmentation2D Panoptic Segmentation3D Semantic SegmentationDomain Adaptation