Hugging Face Trending Papers August 11, 2026

Embedding Rotation Invariance for Provable Multi-Oriented Scene Text Recognition

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Multi-oriented text is ubiquitous in real-world scenes and remains a major challenge for scene text recognition (STR). Existing rotation-aware methods explicitly estimate text orientation.

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Hugging Face Trending Papers

Jun 23

REDI-Match: Rotation-Equivariant Distillation for Efficient and Robust Dense Matching

Vision Foundation Models (VFMs) have significantly advanced dense feature matching, yet severe in-plane rotation remains a critical challenge. Existing solutions face a fundamental dilemma: data-driven methods require inefficient parameter scaling to implicitly learn rotations, whereas strictly equivariant networks lack the semantic capacity of modern VFMs.

efficiency benchmarks safety

arXiv Computer Vision

Sep 25

MEVL-STP: Multi-Encoder and Vision Language Model for Arbitrarily Shaped Scene Text Spotting

MEVL-STP introduces a two‑stage pipeline for spotting arbitrarily shaped scene text. The detection stage fuses features from six frozen vision encoders via a hierarchical Feature Pyramid Network and a Progressive Scale Expansion network to produce precise polygon masks. The recognition stage then crops these masks and feeds them to a fine‑tuned Qwen3‑VL‑8B‑Instruct model, achieving state‑of‑the‑art detection and end‑to‑end performance on CTW1500, Total‑Text, and ICDAR 2015 without synthetic pretraining.

By Aman Anand, Partha Pratim Roy, Shivakumara Palaiahnakote

llms computer-vision fine-tuning multimodal

arXiv Computer Vision

Aug 25

Arbitrarily Shaped Scene Text Detection: A Decade of Advances and Systematic Analysis

arXiv:2107.11800v2 Announce Type: replace Abstract: Scene text detection has become an important research area in computer vision. However, dynamic changes in scenes and the complex diversity of text...

By Pengwen Dai, Feiyang He, Chaolang Li, Xugong Qin, Wenqi Ren, Xiaochun Cao

computer-vision benchmarks

arXiv AI

Jun 2

A Lightweight Context-Driven Training-Free Network for Scene Text Segmentation and Recognition

arXiv:2503. 15639v2 Announce Type: replace-cross Abstract: Modern scene text recognition systems often depend on large end-to-end architectures that require extensive training and are prohibitively expensive for real-time scenarios.

By Ritabrata Chakraborty, Shivakumara Palaiahnakote, Umapada Pal, Cheng-Lin Liu

computer-vision benchmarks

Hugging Face Trending Papers

Jun 23

Advancing WordArt-Oriented Scene Text Recognition: Datasets and Methods

WordArt (artistic text) features highly customized fonts, textures, and layouts, making WordArt-oriented scene TExt Recognition (WATER) substantially more challenging than general Scene Text Recognition (STR). Existing STR datasets and methods, typically built around regular scene text and fixed-template inputs, struggle to scale to WATER.

llms computer-vision multimodal benchmarks

arXiv AI

Jun 30

UniMotion: A Unified Framework for Motion-Text-Vision Understanding and Generation

arXiv:2603. 22282v2 Announce Type: replace-cross Abstract: We present UniMotion, to our knowledge the first unified framework for simultaneous understanding and generation of human motion, natural language, and RGB images within a single architecture.

By Ziyi Wang, Xinshun Wang, Shuang Chen, Yang Cong, Mengyuan Liu

llms nlp efficiency multimodal benchmarks safety