321 citations · 1.8k across the 66 of their papers we have counts for
49 papers · 1 filter
Few-Shot Rotation-Invariant Aerial Image Semantic Segmentation
Qinglong Cao, Yuntian Chen, Chao Ma +1
Few-shot aerial image segmentation is a challenging task that involves precisely parsing objects in query aerial images with limited annotated support. Conventional matching method…
Perceptual Quality Assessment of Omnidirectional Images
Huiyu Duan, Guangtao Zhai, Xiongkuo Min +3
Omnidirectional images and videos can provide immersive experience of real-world scenes in Virtual Reality (VR) environment. We present a perceptual omnidirectional image quality a…
Facial Geometric Detail Recovery via Implicit Representation
Xingyu Ren, Alexandros Lattas, Baris Gecer +4
Learning a dense 3D model with fine-scale details from a single facial image is highly challenging and ill-posed. To address this problem, many approaches fit smooth geometries thr…
DialogueNeRF: Towards Realistic Avatar Face-to-Face Conversation Video Generation
Yichao Yan, Zanwei Zhou, Zi Wang +2
Conversation is an essential component of virtual avatar activities in the metaverse. With the development of natural language processing, textual and vocal conversation generation…
DFA-NeRF: Personalized Talking Head Generation via Disentangled Face Attributes Neural Rendering
Shunyu Yao, RuiZhe Zhong, Yichao Yan +2
While recent advances in deep neural networks have made it possible to render high-quality images, generating photo-realistic and personalized talking head remains challenging. Wit…
Fully Context-Aware Image Inpainting with a Learned Semantic Pyramid
Wendong Zhang, Yunbo Wang, Bingbing Ni +1
Restoring reasonable and realistic content for arbitrary missing regions in images is an important yet challenging task. Although recent image inpainting models have made significa…
TAL: Two-stream Adaptive Learning for Generalizable Person Re-identification
Yichao Yan, Junjie Li, Shengcai Liao +3
Domain generalizable person re-identification aims to apply a trained model to unseen domains. Prior works either combine the data in all the training domains to capture domain-inv…
Out-of-Domain Human Mesh Reconstruction via Dynamic Bilevel Online Adaptation
Shanyan Guan, Jingwei Xu, Michelle Z. He +3
We consider a new problem of adapting a human mesh reconstruction model to out-of-domain streaming videos, where performance of existing SMPL-based models are significantly affecte…
ZARTS: On Zero-order Optimization for Neural Architecture Search
Xiaoxing Wang, Wenxuan Guo, Junchi Yan +2
Differentiable architecture search (DARTS) has been a popular one-shot paradigm for NAS due to its high efficiency. It introduces trainable architecture parameters to represent the…
Efficient Person Search: An Anchor-Free Approach
Yichao Yan, Jinpeng Li, Jie Qin +2
Person search aims to simultaneously localize and identify a query person from realistic, uncropped images. To achieve this goal, state-of-the-art models typically add a re-id bran…
Learning to Track Objects from Unlabeled Videos
Jilai Zheng, Chao Ma, Houwen Peng +1
In this paper, we propose to learn an Unsupervised Single Object Tracker (USOT) from scratch. We identify that three major challenges, i.e., moving object discovery, rich temporal…
Local-to-Global Self-Attention in Vision Transformers
Jinpeng Li, Yichao Yan, Shengcai Liao +2
Transformers have demonstrated great potential in computer vision tasks. To avoid dense computations of self-attentions in high-resolution visual data, some recent Transformer mode…
Task-Specific Normalization for Continual Learning of Blind Image Quality Models
Weixia Zhang, Kede Ma, Guangtao Zhai +1
In this paper, we present a simple yet effective continual learning method for blind image quality assessment (BIQA) with improved quality prediction accuracy, plasticity-stability…
Context-Aware Image Inpainting with Learned Semantic Priors
Wendong Zhang, Junwei Zhu, Ying Tai +5
Recent advances in image inpainting have shown impressive results for generating plausible visual details on rather simple backgrounds. However, for complex scenes, it is still cha…
Making CNNs Interpretable by Building Dynamic Sequential Decision Forests with Top-down Hierarchy Learning
Yilin Wang, Shaozuo Yu, Xiaokang Yang +1
In this paper, we propose a generic model transfer scheme to make Convlutional Neural Networks (CNNs) interpretable, while maintaining their high classification accuracy. We achiev…
Exploring Visual Context for Weakly Supervised Person Search
Yichao Yan, Jinpeng Li, Shengcai Liao +4
Person search has recently emerged as a challenging task that jointly addresses pedestrian detection and person re-identification. Existing approaches follow a fully supervised set…
Learning Multi-Attention Context Graph for Group-Based Re-Identification
Yichao Yan, Jie Qin, Bingbing Ni +6
Learning to re-identify or retrieve a group of people across non-overlapped camera systems has important applications in video surveillance. However, most existing methods focus on…
Bilevel Online Adaptation for Out-of-Domain Human Mesh Reconstruction
Shanyan Guan, Jingwei Xu, Yunbo Wang +2
This paper considers a new problem of adapting a pre-trained model of human mesh reconstruction to out-of-domain streaming videos. However, most previous methods based on the param…
IoU Attack: Towards Temporally Coherent Black-Box Adversarial Attack for Visual Object Tracking
Shuai Jia, Yibing Song, Chao Ma +1
Adversarial attack arises due to the vulnerability of deep neural networks to perceive input samples injected with imperceptible perturbations. Recently, adversarial attack has bee…
Learning Comprehensive Motion Representation for Action Recognition
Mingyu Wu, Boyuan Jiang, Donghao Luo +7
For action recognition learning, 2D CNN-based methods are efficient but may yield redundant features due to applying the same 2D convolution kernel to each frame. Recent efforts at…
Continual Learning for Blind Image Quality Assessment
Weixia Zhang, Dingquan Li, Chao Ma +3
The explosive growth of image data facilitates the fast development of image processing and computer vision methods for emerging visual applications, meanwhile introducing novel di…
DS-Net: Dynamic Spatiotemporal Network for Video Salient Object Detection
Jing Liu, Jiaxiang Wang, Weikang Wang +1
As moving objects always draw more attention of human eyes, the temporal motive information is always exploited complementarily with spatial information to detect salient objects i…
Language-guided Navigation via Cross-Modal Grounding and Alternate Adversarial Learning
Weixia Zhang, Chao Ma, Qi Wu +1
The emerging vision-and-language navigation (VLN) problem aims at learning to navigate an agent to the target location in unseen photo-realistic environments according to the given…
Hierarchical Style-based Networks for Motion Synthesis
Jingwei Xu, Huazhe Xu, Bingbing Ni +3
Generating diverse and natural human motion is one of the long-standing goals for creating intelligent characters in the animated world. In this paper, we propose a self-supervised…