Papers › Text Spotting Transformers

Text Spotting Transformers

5 Apr 2022CVPR 2022 1arXiv:2204.01918archive 2025-07-28

Xiang Zhang, Yongwen Su, Subarna Tripathi, Zhuowen Tu

In this paper, we present TExt Spotting TRansformers (TESTR), a generic end-to-end text spotting framework using Transformers for text detection and recognition in the wild. TESTR builds upon a single encoder and dual decoders for the joint text-box control point regression and character recognition. Other than most existing literature, our method is free from Region-of-Interest operations and heuristics-driven post-processing procedures; TESTR is particularly effective when dealing with curved text-boxes where special cares are needed for the adaptation of the traditional bounding-box representations. We show our canonical representation of control points suitable for text instances in both Bezier curve and polygon annotations. In addition, we design a bounding-box guided polygon detection (box-to-polygon) process. Experiments on curved and arbitrarily shaped datasets demonstrate state-of-the-art performances of the proposed TESTR algorithm.

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DeformableCompositeTransformerDecoder mlpc-ucsd/TESTR/adet/modeling/testr/models.py official repository ran Apache-2.0 (permissive) · d390248d94c9ed63 · report
NestedTensor mlpc-ucsd/TESTR/adet/modeling/testr/models.py official repository ran Apache-2.0 (permissive) · d515f52b31b887cc · report
PositionalEncoding1D mlpc-ucsd/TESTR/adet/modeling/testr/models.py official repository ran fingerprinted Apache-2.0 (permissive) · f77cafa6068b7559 · report
_MSDeformAttnFunction mlpc-ucsd/TESTR/adet/modeling/testr/models.py official repository ran Apache-2.0 (permissive) · 959e178e913b90c4 · report
inverse_sigmoid_offset mlpc-ucsd/TESTR/adet/modeling/testr/models.py official repository ran · fixture could not drive it fingerprinted Apache-2.0 (permissive) · e15093f6736408d0 · report
nested_tensor_from_tensor_list mlpc-ucsd/TESTR/adet/modeling/testr/models.py official repository ran · our draft was wrong Apache-2.0 (permissive) · 874889b24390cf77 · report
sigmoid_offset mlpc-ucsd/TESTR/adet/modeling/testr/models.py official repository ran · fixture could not drive it fingerprinted Apache-2.0 (permissive) · 7430fe026bcbe067 · report
DeformableCompositeTransformerDecoderLayer mlpc-ucsd/TESTR/adet/modeling/testr/models.py official repository unverified Apache-2.0 (permissive) · 45aa5f258a89a820 · report
DeformableTransformer mlpc-ucsd/TESTR/adet/modeling/testr/models.py official repository unverified Apache-2.0 (permissive) · d38f59f1328eb490 · report
DeformableTransformerEncoderLayer mlpc-ucsd/TESTR/adet/modeling/testr/models.py official repository unverified Apache-2.0 (permissive) · a9154eacf08507d1 · report
MSDeformAttn mlpc-ucsd/TESTR/adet/modeling/testr/models.py official repository unverified Apache-2.0 (permissive) · debe8b805c7fb525 · report
TESTR mlpc-ucsd/TESTR/adet/modeling/testr/models.py official repository unverified Apache-2.0 (permissive) · 570d37f8635c97aa · report

Tasks

Text DetectionText Spotting

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Text Spotting ICDAR 2015 TESTR F-measure (%) - Generic Lexicon 73.6 #6 of 18 Archive leaderboard report
Text Spotting ICDAR 2015 TESTR F-measure (%) - Strong Lexicon 85.2 #6 of 18 Archive leaderboard report
Text Spotting ICDAR 2015 TESTR F-measure (%) - Weak Lexicon 79.4 #6 of 18 Archive leaderboard report
Text Spotting Inverse-Text TESTR F-measure (%) - Full Lexicon 41.6 #8 of 9 Archive leaderboard report
Text Spotting Inverse-Text TESTR F-measure (%) - No Lexicon 34.2 #8 of 9 Archive leaderboard report
Text Spotting SCUT-CTW1500 TESTR F-Measure (%) - Full Lexicon 81.5 #9 of 11 Archive leaderboard report
Text Spotting SCUT-CTW1500 TESTR F-measure (%) - No Lexicon 56.0 #9 of 11 Archive leaderboard report
Text Spotting Total-Text TESTR F-measure (%) - Full Lexicon 83.9 #9 of 12 Archive leaderboard report
Text Spotting Total-Text TESTR F-measure (%) - No Lexicon 73.3 #9 of 12 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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