activity
20152025
most citedDAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR

400 citations · 811 across the 31 of their papers we have counts for

collaborators

32 papers

cs.CV2025

Señorita-2M: A High-Quality Instruction-based Dataset for General Video Editing by Video Specialists

Bojia Zi, Penghui Ruan, Marco Chen +7

Recent advancements in video generation have spurred the development of video editing techniques, which can be divided into inversion-based and end-to-end methods. However, current…

cs.CV2024

Elucidating the design space of language models for image generation

Xuantong Liu, Shaozhe Hao, Xianbiao Qi +4

The success of autoregressive (AR) language models in text generation has inspired the computer vision community to adopt Large Language Models (LLMs) for image generation. However…

cs.CV2024

BiGR: Harnessing Binary Latent Codes for Image Generation and Improved Visual Representation Capabilities

Shaozhe Hao, Xuantong Liu, Xianbiao Qi +5

We introduce BiGR, a novel conditional image generation model using compact binary latent codes for generative training, focusing on enhancing both generation and representation ca…

cs.CV2024★ 1 cited

CoCoCo: Improving Text-Guided Video Inpainting for Better Consistency, Controllability and Compatibility

Bojia Zi, Shihao Zhao, Xianbiao Qi +6

Recent advancements in video generation have been remarkable, yet many existing methods struggle with issues of consistency and poor text-video alignment. Moreover, the field lacks…

cs.CL2023★ 4 cited

AcademicGPT: Empowering Academic Research

Shufa Wei, Xiaolong Xu, Xianbiao Qi +21

Large Language Models (LLMs) have demonstrated exceptional capabilities across various natural language processing tasks. Yet, many of these advanced LLMs are tailored for broad, g…

cs.CV2023★ 2 cited

TOSS:High-quality Text-guided Novel View Synthesis from a Single Image

Yukai Shi, Jianan Wang, He Cao +7

In this paper, we present TOSS, which introduces text to the task of novel view synthesis (NVS) from just a single RGB image. While Zero-1-to-3 has demonstrated impressive zero-sho…

cs.LG2023★ 8 cited

Delta-LoRA: Fine-Tuning High-Rank Parameters with the Delta of Low-Rank Matrices

Bojia Zi, Xianbiao Qi, Lingzhi Wang +3

In this paper, we present Delta-LoRA, which is a novel parameter-efficient approach to fine-tune large language models (LLMs). In contrast to LoRA and other low-rank adaptation met…

cs.CV2023★ 15 cited

detrex: Benchmarking Detection Transformers

Tianhe Ren, Shilong Liu, Feng Li +13

The DEtection TRansformer (DETR) algorithm has received considerable attention in the research community and is gradually emerging as a mainstream approach for object detection and…

cs.CV2023★ 20 cited

DreamTime: An Improved Optimization Strategy for Diffusion-Guided 3D Generation

Yukun Huang, Jianan Wang, Yukai Shi +3

Text-to-image diffusion models pre-trained on billions of image-text pairs have recently enabled 3D content creation by optimizing a randomly initialized differentiable 3D represen…

cs.LG2023

Understanding Optimization of Deep Learning via Jacobian Matrix and Lipschitz Constant

Xianbiao Qi, Jianan Wang, Lei Zhang

This article provides a comprehensive understanding of optimization in deep learning, with a primary focus on the challenges of gradient vanishing and gradient exploding, which nor…

cs.CV2023★ 16 cited

DreamWaltz: Make a Scene with Complex 3D Animatable Avatars

Yukun Huang, Jianan Wang, Ailing Zeng +5

We present DreamWaltz, a novel framework for generating and animating complex 3D avatars given text guidance and parametric human body prior. While recent methods have shown encour…

cs.CV2023★ 4 cited

LipsFormer: Introducing Lipschitz Continuity to Vision Transformers

Xianbiao Qi, Jianan Wang, Yihao Chen +2

We present a Lipschitz continuous Transformer, called LipsFormer, to pursue training stability both theoretically and empirically for Transformer-based models. In contrast to previ…

cs.CV2023★ 1 cited

DisCo-CLIP: A Distributed Contrastive Loss for Memory Efficient CLIP Training

Yihao Chen, Xianbiao Qi, Jianan Wang +1

We propose DisCo-CLIP, a distributed memory-efficient CLIP training approach, to reduce the memory consumption of contrastive loss when training contrastive learning models. Our ap…

cs.CV2022★ 7 cited

Exploring Vision Transformers as Diffusion Learners

He Cao, Jianan Wang, Tianhe Ren +4

Score-based diffusion models have captured widespread attention and funded fast progress of recent vision generative tasks. In this paper, we focus on diffusion model backbone whic…

cs.CV2022★ 400 cited

DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR

Shilong Liu, Feng Li, Hao Zhang +5

We present in this paper a novel query formulation using dynamic anchor boxes for DETR (DEtection TRansformer) and offer a deeper understanding of the role of queries in DETR. This…

cs.CV2021★ 6 cited

1st Place Solution for ICDAR 2021 Competition on Mathematical Formula Detection

Yuxiang Zhong, Xianbiao Qi, Shanjun Li +4

In this technical report, we present our 1st place solution for the ICDAR 2021 competition on mathematical formula detection (MFD). The MFD task has three key challenges including…

cs.CV2021★ 3 cited

Winner Team Mia at TextVQA Challenge 2021: Vision-and-Language Representation Learning with Pre-trained Sequence-to-Sequence Model

Yixuan Qiao, Hao Chen, Jun Wang +7

TextVQA requires models to read and reason about text in images to answer questions about them. Specifically, models need to incorporate a new modality of text present in the image…

cs.CV2021★ 32 cited

PingAn-VCGroup's Solution for ICDAR 2021 Competition on Scientific Literature Parsing Task B: Table Recognition to HTML

Jiaquan Ye, Xianbiao Qi, Yelin He +4

This paper presents our solution for ICDAR 2021 competition on scientific literature parsing taskB: table recognition to HTML. In our method, we divide the table content recognitio…

cs.CV2021★ 7 cited

PingAn-VCGroup's Solution for ICDAR 2021 Competition on Scientific Table Image Recognition to Latex

Yelin He, Xianbiao Qi, Jiaquan Ye +5

This paper presents our solution for the ICDAR 2021 Competition on Scientific Table Image Recognition to LaTeX. This competition has two sub-tasks: Table Structure Reconstruction (…

cs.LG2020★ 12 cited

Learning Graph Normalization for Graph Neural Networks

Yihao Chen, Xin Tang, Xianbiao Qi +2

Graph Neural Networks (GNNs) have attracted considerable attention and have emerged as a new promising paradigm to process graph-structured data. GNNs are usually stacked to multip…

cs.CV2020★ 6 cited

Hamming OCR: A Locality Sensitive Hashing Neural Network for Scene Text Recognition

Bingcong Li, Xin Tang, Xianbiao Qi +2

Recently, inspired by Transformer, self-attention-based scene text recognition approaches have achieved outstanding performance. However, we find that the size of model expands rap…

cs.CV2020★ 14 cited

PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networks

Wenwen Yu, Ning Lu, Xianbiao Qi +2

Computer vision with state-of-the-art deep learning models has achieved huge success in the field of Optical Character Recognition (OCR) including text detection and recognition ta…

cs.CV2020★ 1 cited

Neural Mesh Refiner for 6-DoF Pose Estimation

Di Wu, Yihao Chen, Xianbiao Qi +3

How can we effectively utilise the 2D monocular image information for recovering the 6D pose (6-DoF) of the visual objects? Deep learning has shown to be effective for robust and r…

cs.CV2019★ 198 cited

MASTER: Multi-Aspect Non-local Network for Scene Text Recognition

Ning Lu, Wenwen Yu, Xianbiao Qi +4

Attention-based scene text recognizers have gained huge success, which leverages a more compact intermediate representation to learn 1d- or 2d- attention by a RNN-based encoder-dec…