250 citations · 885 across the 14 of their papers we have counts for
15 papers
Rendering-in-the-Loop: An Execution-Driven Agent for Interactive Web Development
Yilong Guo, Hanqi Chen, Zixiao Ye +3
Multimodal large language models have achieved remarkable progress in front-end web development, generating interactive webpages from multimodal references such as screenshots and…
ERNIE 5.0 Technical Report
Haifeng Wang, Hua Wu, Tian Wu +432
In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio…
Forecasting When to Forecast: Accelerating Diffusion Models with Confidence-Gated Taylor
Xiaoliu Guan, Lielin Jiang, Hanqi Chen +6
Diffusion Transformers (DiTs) have demonstrated remarkable performance in visual generation tasks. However, their low inference speed limits their deployment in low-resource applic…
Sortblock: Similarity-Aware Feature Reuse for Diffusion Model
Hanqi Chen, Xu Zhang, Xiaoliu Guan +4
Diffusion Transformers (DiTs) have demonstrated remarkable generative capabilities, particularly benefiting from Transformer architectures that enhance visual and artistic fidelity…
PP-DocBee2: Improved Baselines with Efficient Data for Multimodal Document Understanding
Kui Huang, Xinrong Chen, Wenyu Lv +3
This report introduces PP-DocBee2, an advanced version of the PP-DocBee, designed to enhance multimodal document understanding. Built on a large multimodal model architecture, PP-D…
SUDER: Self-Improving Unified Large Multimodal Models for Understanding and Generation with Dual Self-Rewards
Jixiang Hong, Yiran Zhang, Guanzhong Wang +3
Building upon large language models (LLMs), recent large multimodal models (LMMs) unify cross-model understanding and generation into a single framework. However, LMMs still strugg…
Enabling Versatile Controls for Video Diffusion Models
Xu Zhang, Hao Zhou, Haoming Qin +5
Despite substantial progress in text-to-video generation, achieving precise and flexible control over fine-grained spatiotemporal attributes remains a significant unresolved challe…
PP-DocBee: Improving Multimodal Document Understanding Through a Bag of Tricks
Feng Ni, Kui Huang, Yao Lu +4
With the rapid advancement of digitalization, various document images are being applied more extensively in production and daily life, and there is an increasingly urgent need for…
RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time Detection Transformer
Wenyu Lv, Yian Zhao, Qinyao Chang +3
In this report, we present RT-DETRv2, an improved Real-Time DEtection TRansformer (RT-DETR). RT-DETRv2 builds upon the previous state-of-the-art real-time detector, RT-DETR, and op…
DETRs Beat YOLOs on Real-time Object Detection
Yian Zhao, Wenyu Lv, Shangliang Xu +5
The YOLO series has become the most popular framework for real-time object detection due to its reasonable trade-off between speed and accuracy. However, we observe that the speed…
PP-YOLOE-R: An Efficient Anchor-Free Rotated Object Detector
Xinxin Wang, Guanzhong Wang, Qingqing Dang +3
Arbitrary-oriented object detection is a fundamental task in visual scenes involving aerial images and scene text. In this report, we present PP-YOLOE-R, an efficient anchor-free r…
PP-YOLOE: An evolved version of YOLO
Shangliang Xu, Xinxin Wang, Wenyu Lv +8
In this report, we present PP-YOLOE, an industrial state-of-the-art object detector with high performance and friendly deployment. We optimize on the basis of the previous PP-YOLOv…
PP-PicoDet: A Better Real-Time Object Detector on Mobile Devices
Guanghua Yu, Qinyao Chang, Wenyu Lv +12
The better accuracy and efficiency trade-off has been a challenging problem in object detection. In this work, we are dedicated to studying key optimizations and neural network arc…
PAFNet: An Efficient Anchor-Free Object Detector Guidance
Ying Xin, Guanzhong Wang, Mingyuan Mao +5
Object detection is a basic but challenging task in computer vision, which plays a key role in a variety of industrial applications. However, object detectors based on deep learnin…
PP-YOLO: An Effective and Efficient Implementation of Object Detector
Xiang Long, Kaipeng Deng, Guanzhong Wang +8
Object detection is one of the most important areas in computer vision, which plays a key role in various practical scenarios. Due to limitation of hardware, it is often necessary…