RGBD20K: A Large-Scale Benchmark for RGB-D Semantic Segmentation

arXiv:2609.29028 · cs.CV · Submitted 2026-09-24 · Read on arXiv

cs.CV

Submitted: 2026-09-24

Updated: 2026-09-24

Terminology

• Benchmark — 35× in this paper · explained in 2 episodes
• Transformer — 12× in this paper · explained in 2 episodes
• Alignment — 7× in this paper · explained in 1 episode
• Ablation — 6× in this paper · explained in 1 episode
• Generalization — 5× in this paper · explained in 13 episodes
• Multi-Head Attention — 5× in this paper
• Arbiter — 4× in this paper · explained in 1 episode
• Consistency — 4× in this paper · explained in 3 episodes
• Fidelity — 4× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Multimodal Fusion — 3× in this paper · explained in 3 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Attention Mechanism — 2× in this paper · explained in 3 episodes
• Feed-Forward Network — 2× in this paper
• Representation Learning — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Dual-Stream Architecture — 1× in this paper · explained in 3 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes

Sources

• LoReTrack: Efficient and Accurate Low-Resolution Transformer Tracking
• DMTrack: Spatio-Temporal Multimodal Tracking via Dual-Adapter
• DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation
• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• Matterport3D: Learning from RGB-D Data in Indoor Environments
• Joint 2D-3D-Semantic Data for Indoor Scene Understanding
• GeminiFusion: Efficient Pixel-wise Multimodal Fusion for Vision Transformer
• DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

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