4 citations · 10 across the 8 of their papers we have counts for
9 papers
Steering Visual Generation in Unified Multimodal Models with Understanding Supervision
Zeyu Liu, Zanlin Ni, Yang Yue +5
Unified multimodal models are envisioned to bridge the gap between understanding and generation. Yet, to achieve competitive performance, state-of-the-art models adopt largely deco…
ResTok: Learning Hierarchical Residuals in 1D Visual Tokenizers for Autoregressive Image Generation
Xu Zhang, Cheng Da, Huan Yang +3
Existing 1D visual tokenizers for autoregressive (AR) generation largely follow the design principles of language modeling, as they are built directly upon transformers whose prior…
Diffusion Model as a Noise-Aware Latent Reward Model for Step-Level Preference Optimization
Tao Zhang, Cheng Da, Kun Ding +7
Preference optimization for diffusion models aims to align them with human preferences for images. Previous methods typically use Vision-Language Models (VLMs) as pixel-level rewar…
Vision Grid Transformer for Document Layout Analysis
Cheng Da, Chuwei Luo, Qi Zheng +1
Document pre-trained models and grid-based models have proven to be very effective on various tasks in Document AI. However, for the document layout analysis (DLA) task, existing d…
LISTER: Neighbor Decoding for Length-Insensitive Scene Text Recognition
Changxu Cheng, Peng Wang, Cheng Da +2
The diversity in length constitutes a significant characteristic of text. Due to the long-tail distribution of text lengths, most existing methods for scene text recognition (STR)…
Multi-Granularity Prediction with Learnable Fusion for Scene Text Recognition
Cheng Da, Peng Wang, Cong Yao
Due to the enormous technical challenges and wide range of applications, scene text recognition (STR) has been an active research topic in computer vision for years. To tackle this…
Multi-Granularity Prediction for Scene Text Recognition
Peng Wang, Cheng Da, Cong Yao
Scene text recognition (STR) has been an active research topic in computer vision for years. To tackle this challenging problem, numerous innovative methods have been successively…
Levenshtein OCR
Cheng Da, Peng Wang, Cong Yao
A novel scene text recognizer based on Vision-Language Transformer (VLT) is presented. Inspired by Levenshtein Transformer in the area of NLP, the proposed method (named Levenshtei…
Fashion Focus: Multi-modal Retrieval System for Video Commodity Localization in E-commerce
Yanhao Zhang, Qiang Wang, Pan Pan +4
Nowadays, live-stream and short video shopping in E-commerce have grown exponentially. However, the sellers are required to manually match images of the selling products to the tim…