59 citations · 446 across the 85 of their papers we have counts for
43 papers · 1 filter
CoSeR: Bridging Image and Language for Cognitive Super-Resolution
Haoze Sun, Wenbo Li, Jianzhuang Liu +5
Existing super-resolution (SR) models primarily focus on restoring local texture details, often neglecting the global semantic information within the scene. This oversight can lead…
Universal Segmentation at Arbitrary Granularity with Language Instruction
Yong Liu, Cairong Zhang, Yitong Wang +3
This paper aims to achieve universal segmentation of arbitrary semantic level. Despite significant progress in recent years, specialist segmentation approaches are limited to speci…
ToonTalker: Cross-Domain Face Reenactment
Yuan Gong, Yong Zhang, Xiaodong Cun +5
We target cross-domain face reenactment in this paper, i.e., driving a cartoon image with the video of a real person and vice versa. Recently, many works have focused on one-shot t…
Efficient Text-Guided 3D-Aware Portrait Generation with Score Distillation Sampling on Distribution
Yiji Cheng, Fei Yin, Xiaoke Huang +5
Text-to-3D is an emerging task that allows users to create 3D content with infinite possibilities. Existing works tackle the problem by optimizing a 3D representation with guidance…
Global and Local Semantic Completion Learning for Vision-Language Pre-training
Rong-Cheng Tu, Yatai Ji, Jie Jiang +6
Cross-modal alignment plays a crucial role in vision-language pre-training (VLP) models, enabling them to capture meaningful associations across different modalities. For this purp…
TaleCrafter: Interactive Story Visualization with Multiple Characters
Yuan Gong, Youxin Pang, Xiaodong Cun +8
Accurate Story visualization requires several necessary elements, such as identity consistency across frames, the alignment between plain text and visual content, and a reasonable…
SOC: Semantic-Assisted Object Cluster for Referring Video Object Segmentation
Zhuoyan Luo, Yicheng Xiao, Yong Liu +5
This paper studies referring video object segmentation (RVOS) by boosting video-level visual-linguistic alignment. Recent approaches model the RVOS task as a sequence prediction pr…
Meta-Auxiliary Network for 3D GAN Inversion
Bangrui Jiang, Zhenhua Guo, Yujiu Yang
Real-world image manipulation has achieved fantastic progress in recent years. GAN inversion, which aims to map the real image to the latent code faithfully, is the first step in t…
Accelerating Diffusion Models for Inverse Problems through Shortcut Sampling
Gongye Liu, Haoze Sun, Jiayi Li +2
Diffusion models have recently demonstrated an impressive ability to address inverse problems in an unsupervised manner. While existing methods primarily focus on modifying the pos…
Assessor360: Multi-sequence Network for Blind Omnidirectional Image Quality Assessment
Tianhe Wu, Shuwei Shi, Haoming Cai +4
Blind Omnidirectional Image Quality Assessment (BOIQA) aims to objectively assess the human perceptual quality of omnidirectional images (ODIs) without relying on pristine-quality…
RIFormer: Keep Your Vision Backbone Effective While Removing Token Mixer
Jiahao Wang, Songyang Zhang, Yong Liu +6
This paper studies how to keep a vision backbone effective while removing token mixers in its basic building blocks. Token mixers, as self-attention for vision transformers (ViTs),…
Global Knowledge Calibration for Fast Open-Vocabulary Segmentation
Kunyang Han, Yong Liu, Jun Hao Liew +8
Recent advancements in pre-trained vision-language models, such as CLIP, have enabled the segmentation of arbitrary concepts solely from textual inputs, a process commonly referred…
Multimodal Prototype-Enhanced Network for Few-Shot Action Recognition
Xinzhe Ni, Yong Liu, Hao Wen +3
Current methods for few-shot action recognition mainly fall into the metric learning framework following ProtoNet, which demonstrates the importance of prototypes. Although they ac…
GLeaD: Improving GANs with A Generator-Leading Task
Qingyan Bai, Ceyuan Yang, Yinghao Xu +3
Generative adversarial network (GAN) is formulated as a two-player game between a generator (G) and a discriminator (D), where D is asked to differentiate whether an image comes fr…
3D GAN Inversion with Facial Symmetry Prior
Fei Yin, Yong Zhang, Xuan Wang +8
Recently, a surge of high-quality 3D-aware GANs have been proposed, which leverage the generative power of neural rendering. It is natural to associate 3D GANs with GAN inversion m…
Seeing What You Miss: Vision-Language Pre-training with Semantic Completion Learning
Yatai Ji, Rongcheng Tu, Jie Jiang +6
Cross-modal alignment is essential for vision-language pre-training (VLP) models to learn the correct corresponding information across different modalities. For this purpose, inspi…
Global Spectral Filter Memory Network for Video Object Segmentation
Yong Liu, Ran Yu, Jiahao Wang +4
This paper studies semi-supervised video object segmentation through boosting intra-frame interaction. Recent memory network-based methods focus on exploiting inter-frame temporal…
MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training Model
Yatai Ji, Junjie Wang, Yuan Gong +6
Multimodal semantic understanding often has to deal with uncertainty, which means the obtained messages tend to refer to multiple targets. Such uncertainty is problematic for our i…
Towards Real-World Video Deblurring by Exploring Blur Formation Process
Mingdeng Cao, Zhihang Zhong, Yanbo Fan +5
This paper aims at exploring how to synthesize close-to-real blurs that existing video deblurring models trained on them can generalize well to real-world blurry videos. In recent…
Modelling Latent Dynamics of StyleGAN using Neural ODEs
Weihao Xia, Yujiu Yang, Jing-Hao Xue
In this paper, we propose to model the video dynamics by learning the trajectory of independently inverted latent codes from GANs. The entire sequence is seen as discrete-time obse…
Learning Quality-aware Dynamic Memory for Video Object Segmentation
Yong Liu, Ran Yu, Fei Yin +4
Recently, several spatial-temporal memory-based methods have verified that storing intermediate frames and their masks as memory are helpful to segment target objects in videos. Ho…
Rethinking Alignment in Video Super-Resolution Transformers
Shuwei Shi, Jinjin Gu, Liangbin Xie +3
The alignment of adjacent frames is considered an essential operation in video super-resolution (VSR). Advanced VSR models, including the latest VSR Transformers, are generally equ…
Learning Adaptive Warping for Real-World Rolling Shutter Correction
Mingdeng Cao, Zhihang Zhong, Jiahao Wang +2
This paper proposes the first real-world rolling shutter (RS) correction dataset, BS-RSC, and a corresponding model to correct the RS frames in a distorted video. Mobile devices in…
Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network
Shanshan Lao, Yuan Gong, Shuwei Shi +5
Image quality assessment (IQA) algorithm aims to quantify the human perception of image quality. Unfortunately, there is a performance drop when assessing the distortion images gen…