216 citations · 1.4k across the 66 of their papers we have counts for
59 papers · 1 filter
WildRefer: 3D Object Localization in Large-scale Dynamic Scenes with Multi-modal Visual Data and Natural Language
Zhenxiang Lin, Xidong Peng, Peishan Cong +6
We introduce the task of 3D visual grounding in large-scale dynamic scenes based on natural linguistic descriptions and online captured multi-modal visual data, including 2D images…
Lite Vision Transformer with Enhanced Self-Attention
Chenglin Yang, Yilin Wang, Jianming Zhang +4
Despite the impressive representation capacity of vision transformer models, current light-weight vision transformer models still suffer from inconsistent and incorrect dense predi…
SketchEdit: Mask-Free Local Image Manipulation with Partial Sketches
Yu Zeng, Zhe Lin, Vishal M. Patel
Sketch-based image manipulation is an interactive image editing task to modify an image based on input sketches from users. Existing methods typically formulate this task as a cond…
Multi-Scale Aligned Distillation for Low-Resolution Detection
Lu Qi, Jason Kuen, Jiuxiang Gu +5
In instance-level detection tasks (e.g., object detection), reducing input resolution is an easy option to improve runtime efficiency. However, this option traditionally hurts the…
SSH: A Self-Supervised Framework for Image Harmonization
Yifan Jiang, He Zhang, Jianming Zhang +7
Image harmonization aims to improve the quality of image compositing by matching the "appearance" (\eg, color tone, brightness and contrast) between foreground and background image…
Multimodal Contrastive Training for Visual Representation Learning
Xin Yuan, Zhe Lin, Jason Kuen +5
We develop an approach to learning visual representations that embraces multimodal data, driven by a combination of intra- and inter-modal similarity preservation objectives. Unlik…
Going Deeper Into Face Detection: A Survey
Shervin Minaee, Ping Luo, Zhe Lin +1
Face detection is a crucial first step in many facial recognition and face analysis systems. Early approaches for face detection were mainly based on classifiers built on top of ha…
Content-Aware GAN Compression
Yuchen Liu, Zhixin Shu, Yijun Li +3
Generative adversarial networks (GANs), e.g., StyleGAN2, play a vital role in various image generation and synthesis tasks, yet their notoriously high computational cost hinders th…
ALADIN: All Layer Adaptive Instance Normalization for Fine-grained Style Similarity
Dan Ruta, Saeid Motiian, Baldo Faieta +5
We present ALADIN (All Layer AdaIN); a novel architecture for searching images based on the similarity of their artistic style. Representation learning is critical to visual search…
Meticulous Object Segmentation
Chenglin Yang, Yilin Wang, Jianming Zhang +3
Compared with common image segmentation tasks targeted at low-resolution images, higher resolution detailed image segmentation receives much less attention. In this paper, we propo…
Semantic Layout Manipulation with High-Resolution Sparse Attention
Haitian Zheng, Zhe Lin, Jingwan Lu +4
We tackle the problem of semantic image layout manipulation, which aims to manipulate an input image by editing its semantic label map. A core problem of this task is how to transf…
Mask Guided Matting via Progressive Refinement Network
Qihang Yu, Jianming Zhang, He Zhang +5
We propose Mask Guided (MG) Matting, a robust matting framework that takes a general coarse mask as guidance. MG Matting leverages a network (PRN) design which encourages the matti…
Deep Image Compositing
He Zhang, Jianming Zhang, Federico Perazzi +2
Image compositing is a task of combining regions from different images to compose a new image. A common use case is background replacement of portrait images. To obtain high qualit…
CR-Fill: Generative Image Inpainting with Auxiliary Contexutal Reconstruction
Yu Zeng, Zhe Lin, Huchuan Lu +1
Recent deep generative inpainting methods use attention layers to allow the generator to explicitly borrow feature patches from the known region to complete a missing region. Due t…
Open-Edit: Open-Domain Image Manipulation with Open-Vocabulary Instructions
Xihui Liu, Zhe Lin, Jianming Zhang +4
We propose a novel algorithm, named Open-Edit, which is the first attempt on open-domain image manipulation with open-vocabulary instructions. It is a challenging task considering…
Unselfie: Translating Selfies to Neutral-pose Portraits in the Wild
Liqian Ma, Zhe Lin, Connelly Barnes +2
Due to the ubiquity of smartphones, it is popular to take photos of one's self, or "selfies." Such photos are convenient to take, because they do not require specialized equipment…
Incorporating Reinforced Adversarial Learning in Autoregressive Image Generation
Kenan E. Ak, Ning Xu, Zhe Lin +1
Autoregressive models recently achieved comparable results versus state-of-the-art Generative Adversarial Networks (GANs) with the help of Vector Quantized Variational AutoEncoders…
Real-time Semantic Segmentation with Fast Attention
Ping Hu, Federico Perazzi, Fabian Caba Heilbron +4
In deep CNN based models for semantic segmentation, high accuracy relies on rich spatial context (large receptive fields) and fine spatial details (high resolution), both of which…
High-Resolution Image Inpainting with Iterative Confidence Feedback and Guided Upsampling
Yu Zeng, Zhe Lin, Jimei Yang +3
Existing image inpainting methods often produce artifacts when dealing with large holes in real applications. To address this challenge, we propose an iterative inpainting method w…
Context-Aware Group Captioning via Self-Attention and Contrastive Features
Zhuowan Li, Quan Tran, Long Mai +2
While image captioning has progressed rapidly, existing works focus mainly on describing single images. In this paper, we introduce a new task, context-aware group captioning, whic…
Temporally Distributed Networks for Fast Video Semantic Segmentation
Ping Hu, Fabian Caba Heilbron, Oliver Wang +3
We present TDNet, a temporally distributed network designed for fast and accurate video semantic segmentation. We observe that features extracted from a certain high-level layer of…
Scaling Object Detection by Transferring Classification Weights
Jason Kuen, Federico Perazzi, Zhe Lin +2
Large scale object detection datasets are constantly increasing their size in terms of the number of classes and annotations count. Yet, the number of object-level categories annot…
Towards High-Resolution Salient Object Detection
Yi Zeng, Pingping Zhang, Jianming Zhang +2
Deep neural network based methods have made a significant breakthrough in salient object detection. However, they are typically limited to input images with low resolutions ($400\t…
Multitask Text-to-Visual Embedding with Titles and Clickthrough Data
Pranav Aggarwal, Zhe Lin, Baldo Faieta +1
Text-visual (or called semantic-visual) embedding is a central problem in vision-language research. It typically involves mapping of an image and a text description to a common fea…