283 citations · 1.4k across the 72 of their papers we have counts for
17 papers · 1 filter
Improving Visual Quality of Image Synthesis by A Token-based Generator with Transformers
Yanhong Zeng, Huan Yang, Hongyang Chao +2
We present a new perspective of achieving image synthesis by viewing this task as a visual token generation problem. Different from existing paradigms that directly synthesize a fu…
Searching the Search Space of Vision Transformer
Minghao Chen, Kan Wu, Bolin Ni +5
Vision Transformer has shown great visual representation power in substantial vision tasks such as recognition and detection, and thus been attracting fast-growing efforts on manua…
Advancing High-Resolution Video-Language Representation with Large-Scale Video Transcriptions
Hongwei Xue, Tiankai Hang, Yanhong Zeng +5
We study joint video and language (VL) pre-training to enable cross-modality learning and benefit plentiful downstream VL tasks. Existing works either extract low-quality video fea…
A Picture is Worth a Thousand Words: A Unified System for Diverse Captions and Rich Images Generation
Yupan Huang, Bei Liu, Jianlong Fu +1
A creative image-and-text generative AI system mimics humans' extraordinary abilities to provide users with diverse and comprehensive caption suggestions, as well as rich image cre…
Learning Fine-Grained Motion Embedding for Landscape Animation
Hongwei Xue, Bei Liu, Huan Yang +3
In this paper we focus on landscape animation, which aims to generate time-lapse videos from a single landscape image. Motion is crucial for landscape animation as it determines ho…
Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment
Heliang Zheng, Huan Yang, Jianlong Fu +2
An important scenario for image quality assessment (IQA) is to evaluate image restoration (IR) algorithms. The state-of-the-art approaches adopt a full-reference paradigm that comp…
Domain-Aware Universal Style Transfer
Kibeom Hong, Seogkyu Jeon, Huan Yang +2
Style transfer aims to reproduce content images with the styles from reference images. Existing universal style transfer methods successfully deliver arbitrary styles to original i…
Reference-based Defect Detection Network
Zhaoyang Zeng, Bei Liu, Jianlong Fu +1
The defect detection task can be regarded as a realistic scenario of object detection in the computer vision field and it is widely used in the industrial field. Directly applying…
Rethinking and Improving Relative Position Encoding for Vision Transformer
Kan Wu, Houwen Peng, Minghao Chen +2
Relative position encoding (RPE) is important for transformer to capture sequence ordering of input tokens. General efficacy has been proven in natural language processing. However…
AutoFormer: Searching Transformers for Visual Recognition
Minghao Chen, Houwen Peng, Jianlong Fu +1
Recently, pure transformer-based models have shown great potentials for vision tasks such as image classification and detection. However, the design of transformer networks is chal…
Probing Inter-modality: Visual Parsing with Self-Attention for Vision-Language Pre-training
Hongwei Xue, Yupan Huang, Bei Liu +4
Vision-Language Pre-training (VLP) aims to learn multi-modal representations from image-text pairs and serves for downstream vision-language tasks in a fine-tuning fashion. The dom…
LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search
Bin Yan, Houwen Peng, Kan Wu +3
Object tracking has achieved significant progress over the past few years. However, state-of-the-art trackers become increasingly heavy and expensive, which limits their deployment…
Seeing Out of tHe bOx: End-to-End Pre-training for Vision-Language Representation Learning
Zhicheng Huang, Zhaoyang Zeng, Yupan Huang +3
We study joint learning of Convolutional Neural Network (CNN) and Transformer for vision-language pre-training (VLPT) which aims to learn cross-modal alignments from millions of im…
3D Human Body Reshaping with Anthropometric Modeling
Yanhong Zeng, Jianlong Fu, Hongyang Chao
Reshaping accurate and realistic 3D human bodies from anthropometric parameters (e.g., height, chest size, etc.) poses a fundamental challenge for person identification, online sho…
Aggregated Contextual Transformations for High-Resolution Image Inpainting
Yanhong Zeng, Jianlong Fu, Hongyang Chao +1
State-of-the-art image inpainting approaches can suffer from generating distorted structures and blurry textures in high-resolution images (e.g., 512x512). The challenges mainly dr…
One-Shot Neural Ensemble Architecture Search by Diversity-Guided Search Space Shrinking
Minghao Chen, Houwen Peng, Jianlong Fu +1
Despite remarkable progress achieved, most neural architecture search (NAS) methods focus on searching for one single accurate and robust architecture. To further build models with…
Learning Spatio-Temporal Transformer for Visual Tracking
Bin Yan, Houwen Peng, Jianlong Fu +2
In this paper, we present a new tracking architecture with an encoder-decoder transformer as the key component. The encoder models the global spatio-temporal feature dependencies b…