49 citations · 334 across the 30 of their papers we have counts for
30 papers
TinyCLIP: CLIP Distillation via Affinity Mimicking and Weight Inheritance
Kan Wu, Houwen Peng, Zhenghong Zhou +10
In this paper, we propose a novel cross-modal distillation method, called TinyCLIP, for large-scale language-image pre-trained models. The method introduces two core techniques: af…
Learning Profitable NFT Image Diffusions via Multiple Visual-Policy Guided Reinforcement Learning
Huiguo He, Tianfu Wang, Huan Yang +5
We study the task of generating profitable Non-Fungible Token (NFT) images from user-input texts. Recent advances in diffusion models have shown great potential for image generatio…
Semantic-Conditional Diffusion Networks for Image Captioning
Jianjie Luo, Yehao Li, Yingwei Pan +4
Recent advances on text-to-image generation have witnessed the rise of diffusion models which act as powerful generative models. Nevertheless, it is not trivial to exploit such lat…
Out-of-Distribution Detection with Hilbert-Schmidt Independence Optimization
Jingyang Lin, Yu Wang, Qi Cai +4
Outlier detection tasks have been playing a critical role in AI safety. There has been a great challenge to deal with this task. Observations show that deep neural network classifi…
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…
CoCo-BERT: Improving Video-Language Pre-training with Contrastive Cross-modal Matching and Denoising
Jianjie Luo, Yehao Li, Yingwei Pan +3
BERT-type structure has led to the revolution of vision-language pre-training and the achievement of state-of-the-art results on numerous vision-language downstream tasks. Existing…
CORE-Text: Improving Scene Text Detection with Contrastive Relational Reasoning
Jingyang Lin, Yingwei Pan, Rongfeng Lai +3
Localizing text instances in natural scenes is regarded as a fundamental challenge in computer vision. Nevertheless, owing to the extremely varied aspect ratios and scales of text…
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…
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…
A Low Rank Promoting Prior for Unsupervised Contrastive Learning
Yu Wang, Jingyang Lin, Qi Cai +4
Unsupervised learning is just at a tipping point where it could really take off. Among these approaches, contrastive learning has seen tremendous progress and led to state-of-the-a…
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…
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…
Learning Joint Spatial-Temporal Transformations for Video Inpainting
Yanhong Zeng, Jianlong Fu, Hongyang Chao
High-quality video inpainting that completes missing regions in video frames is a promising yet challenging task. State-of-the-art approaches adopt attention models to complete a f…
Endowing Deep 3D Models with Rotation Invariance Based on Principal Component Analysis
Zelin Xiao, Hongxin Lin, Renjie Li +2
In this paper, we propose a simple yet effective method to endow deep 3D models with rotation invariance by expressing the coordinates in an intrinsic frame determined by the objec…
WSOD^2: Learning Bottom-up and Top-down Objectness Distillation for Weakly-supervised Object Detection
Zhaoyang Zeng, Bei Liu, Jianlong Fu +2
We study on weakly-supervised object detection (WSOD) which plays a vital role in relieving human involvement from object-level annotations. Predominant works integrate region prop…
Deep Metric Learning with Density Adaptivity
Yehao Li, Ting Yao, Yingwei Pan +2
The problem of distance metric learning is mostly considered from the perspective of learning an embedding space, where the distances between pairs of examples are in correspondenc…
Justlookup: One Millisecond Deep Feature Extraction for Point Clouds By Lookup Tables
Hongxin Lin, Zelin Xiao, Yang Tan +2
Deep models are capable of fitting complex high dimensional functions while usually yielding large computation load. There is no way to speed up the inference process by classical…
Temporal Deformable Convolutional Encoder-Decoder Networks for Video Captioning
Jingwen Chen, Yingwei Pan, Yehao Li +3
It is well believed that video captioning is a fundamental but challenging task in both computer vision and artificial intelligence fields. The prevalent approach is to map an inpu…
Pointing Novel Objects in Image Captioning
Yehao Li, Ting Yao, Yingwei Pan +2
Image captioning has received significant attention with remarkable improvements in recent advances. Nevertheless, images in the wild encapsulate rich knowledge and cannot be suffi…
Learning Pyramid-Context Encoder Network for High-Quality Image Inpainting
Yanhong Zeng, Jianlong Fu, Hongyang Chao +1
High-quality image inpainting requires filling missing regions in a damaged image with plausible content. Existing works either fill the regions by copying image patches or generat…
Face Recognition from Sequential Sparse 3D Data via Deep Registration
Yang Tan, Hongxin Lin, Zelin Xiao +2
Previous works have shown that face recognition with high accurate 3D data is more reliable and insensitive to pose and illumination variations. Recently, low-cost and portable 3D…
Jointly Localizing and Describing Events for Dense Video Captioning
Yehao Li, Ting Yao, Yingwei Pan +2
Automatically describing a video with natural language is regarded as a fundamental challenge in computer vision. The problem nevertheless is not trivial especially when a video co…
Automatically Building Face Datasets of New Domains from Weakly Labeled Data with Pretrained Models
Shengyong Ding, Junyu Wu, Wei Xu +1
Training data are critical in face recognition systems. However, labeling a large scale face data for a particular domain is very tedious. In this paper, we propose a method to aut…