162 citations · 562 across the 52 of their papers we have counts for
53 papers
Recognize Anything: A Strong Image Tagging Model
Youcai Zhang, Xinyu Huang, Jinyu Ma +9
We present the Recognize Anything Model (RAM): a strong foundation model for image tagging. RAM makes a substantial step for large models in computer vision, demonstrating the zero…
ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation
Jiaming Liu, Senqiao Yang, Peidong Jia +5
Since real-world machine systems are running in non-stationary environments, Continual Test-Time Adaptation (CTTA) task is proposed to adapt the pre-trained model to continually ch…
The 3rd Anti-UAV Workshop & Challenge: Methods and Results
Jian Zhao, Jianan Li, Lei Jin +20
The 3rd Anti-UAV Workshop & Challenge aims to encourage research in developing novel and accurate methods for multi-scale object tracking. The Anti-UAV dataset used for the Anti-UA…
ContrastMotion: Self-supervised Scene Motion Learning for Large-Scale LiDAR Point Clouds
Xiangze Jia, Hui Zhou, Xinge Zhu +3
In this paper, we propose a novel self-supervised motion estimator for LiDAR-based autonomous driving via BEV representation. Different from usually adopted self-supervised strateg…
A Comprehensive Comparison of Projections in Omnidirectional Super-Resolution
Huicheng Pi, Senmao Tian, Ming Lu +3
Super-Resolution (SR) has gained increasing research attention over the past few years. With the development of Deep Neural Networks (DNNs), many super-resolution methods based on…
CABM: Content-Aware Bit Mapping for Single Image Super-Resolution Network with Large Input
Senmao Tian, Ming Lu, Jiaming Liu +3
With the development of high-definition display devices, the practical scenario of Super-Resolution (SR) usually needs to super-resolve large input like 2K to higher resolution (4K…
SGL: Structure Guidance Learning for Camera Localization
Xudong Zhang, Shuang Gao, Xiaohu Nan +7
Camera localization is a classical computer vision task that serves various Artificial Intelligence and Robotics applications. With the rapid developments of Deep Neural Networks (…
Learning Audio-Visual Source Localization via False Negative Aware Contrastive Learning
Weixuan Sun, Jiayi Zhang, Jianyuan Wang +6
Self-supervised audio-visual source localization aims to locate sound-source objects in video frames without extra annotations. Recent methods often approach this goal with the hel…
Box-Level Active Detection
Mengyao Lyu, Jundong Zhou, Hui Chen +7
Active learning selects informative samples for annotation within budget, which has proven efficient recently on object detection. However, the widely used active detection benchma…
PiMAE: Point Cloud and Image Interactive Masked Autoencoders for 3D Object Detection
Anthony Chen, Kevin Zhang, Renrui Zhang +4
Masked Autoencoders learn strong visual representations and achieve state-of-the-art results in several independent modalities, yet very few works have addressed their capabilities…
Tag2Text: Guiding Vision-Language Model via Image Tagging
Xinyu Huang, Youcai Zhang, Jinyu Ma +6
This paper presents Tag2Text, a vision language pre-training (VLP) framework, which introduces image tagging into vision-language models to guide the learning of visual-linguistic…
BEV-SAN: Accurate BEV 3D Object Detection via Slice Attention Networks
Xiaowei Chi, Jiaming Liu, Ming Lu +4
Bird's-Eye-View (BEV) 3D Object Detection is a crucial multi-view technique for autonomous driving systems. Recently, plenty of works are proposed, following a similar paradigm con…
BEV-LGKD: A Unified LiDAR-Guided Knowledge Distillation Framework for BEV 3D Object Detection
Jianing Li, Ming Lu, Jiaming Liu +3
Recently, Bird's-Eye-View (BEV) representation has gained increasing attention in multi-view 3D object detection, which has demonstrated promising applications in autonomous drivin…
BEVUDA: Multi-geometric Space Alignments for Domain Adaptive BEV 3D Object Detection
Jiaming Liu, Rongyu Zhang, Xiaoqi Li +5
Vision-centric bird-eye-view (BEV) perception has shown promising potential in autonomous driving. Recent works mainly focus on improving efficiency or accuracy but neglect the cha…
A Real-Time Fusion Framework for Long-term Visual Localization
Yuchen Yang, Xudong Zhang, Shuang Gao +5
Visual localization is a fundamental task that regresses the 6 Degree Of Freedom (6DoF) poses with image features in order to serve the high precision localization requests in many…
IDEA: Increasing Text Diversity via Online Multi-Label Recognition for Vision-Language Pre-training
Xinyu Huang, Youcai Zhang, Ying Cheng +7
Vision-Language Pre-training (VLP) with large-scale image-text pairs has demonstrated superior performance in various fields. However, the image-text pairs co-occurrent on the Inte…
CrossHuman: Learning Cross-Guidance from Multi-Frame Images for Human Reconstruction
Liliang Chen, Jiaqi Li, Han Huang +1
We propose CrossHuman, a novel method that learns cross-guidance from parametric human model and multi-frame RGB images to achieve high-quality 3D human reconstruction. To recover…
Efficient Meta-Tuning for Content-aware Neural Video Delivery
Xiaoqi Li, Jiaming Liu, Shizun Wang +6
Recently, Deep Neural Networks (DNNs) are utilized to reduce the bandwidth and improve the quality of Internet video delivery. Existing methods train corresponding content-aware su…
BANet: Motion Forecasting with Boundary Aware Network
Chen Zhang, Honglin Sun, Chen Chen +1
We propose a motion forecasting model called BANet, which means Boundary-Aware Network, and it is a variant of LaneGCN. We believe that it is not enough to use only the lane center…
Mixed Sample Augmentation for Online Distillation
Yiqing Shen, Liwu Xu, Yuzhe Yang +2
Mixed Sample Regularization (MSR), such as MixUp or CutMix, is a powerful data augmentation strategy to generalize convolutional neural networks. Previous empirical analysis has il…
Situational Perception Guided Image Matting
Bo Xu, Jiake Xie, Han Huang +4
Most automatic matting methods try to separate the salient foreground from the background. However, the insufficient quantity and subjective bias of the current existing matting da…
Personalized Image Aesthetics Assessment with Rich Attributes
Yuzhe Yang, Liwu Xu, Leida Li +4
Personalized image aesthetics assessment (PIAA) is challenging due to its highly subjective nature. People's aesthetic tastes depend on diversified factors, including image charact…
Self-Distillation from the Last Mini-Batch for Consistency Regularization
Yiqing Shen, Liwu Xu, Yuzhe Yang +2
Knowledge distillation (KD) shows a bright promise as a powerful regularization strategy to boost generalization ability by leveraging learned sample-level soft targets. Yet, emplo…
Structured Local Radiance Fields for Human Avatar Modeling
Zerong Zheng, Han Huang, Tao Yu +3
It is extremely challenging to create an animatable clothed human avatar from RGB videos, especially for loose clothes due to the difficulties in motion modeling. To address this p…