Methods › Computer Vision › Image Models › DPT

Dense Prediction Transformer

DPT

25 papers tagged archive 2025-07-28

Introduced by René Ranftl et al. in Vision Transformers for Dense Prediction

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Dense Prediction Transformers (DPT) are a type of vision transformer for dense prediction tasks.

The input image is transformed into tokens (orange) either by extracting non-overlapping patches followed by a linear projection of their flattened representation (DPT-Base and DPT-Large) or by applying a ResNet-50 feature extractor (DPT-Hybrid). The image embedding is augmented with a positional embedding and a patch-independent readout token (red) is added. The tokens are passed through multiple transformer stages. The tokens are reassembled from different stages into an image-like representation at multiple resolutions (green). Fusion modules (purple) progressively fuse and upsample the representations to generate a fine-grained prediction.

PaperSourceSee Code · intel-isl/DPT

Papers archive 2025-07-28

25 shown of 25, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 53 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Depth Estimation4
In-Context Reinforcement Learning4
Language Modelling4
Monocular Depth Estimation4
Reinforcement Learning3
Semantic Segmentation3
reinforcement-learning3
Classification2
Decision Making2
Image Classification2
In-Context Learning2
Language Modeling2
Object Detection2
Question Answering2
Reinforcement Learning (RL)2
Self-Supervised Learning2
image-classification2
object-detection2
3D Scene Reconstruction1
Autonomous Driving1

Usage over time archive 2025-07-28

Papers per year tagged with DPT: 2021 to 2025, peak 8 8 0 2021: 2 papers 2021 2022: 8 papers 2022 2023: 8 papers 2023 2024: 4 papers 2024 2025: 3 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (25 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Image ModelsVision Transformers

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