128 citations · 197 across the 19 of their papers we have counts for
16 papers · 1 filter
UniG3D: A Unified 3D Object Generation Dataset
Qinghong Sun, Yangguang Li, ZeXiang Liu +5
The field of generative AI has a transformative impact on various areas, including virtual reality, autonomous driving, the metaverse, gaming, and robotics. Among these application…
Mask Hierarchical Features For Self-Supervised Learning
Fenggang Liu, Yangguang Li, Feng Liang +3
This paper shows that Masking the Deep hierarchical features is an efficient self-supervised method, denoted as MaskDeep. MaskDeep treats each patch in the representation space as…
Fast-BEV: Towards Real-time On-vehicle Bird's-Eye View Perception
Bin Huang, Yangguang Li, Enze Xie +7
Recently, the pure camera-based Bird's-Eye-View (BEV) perception removes expensive Lidar sensors, making it a feasible solution for economical autonomous driving. However, most exi…
Parallel Reasoning Network for Human-Object Interaction Detection
Huan Peng, Fenggang Liu, Yangguang Li +4
Human-Object Interaction (HOI) detection aims to learn how human interacts with surrounding objects. Previous HOI detection frameworks simultaneously detect human, objects and thei…
Fast-BEV: A Fast and Strong Bird's-Eye View Perception Baseline
Yangguang Li, Bin Huang, Zeren Chen +8
Recently, perception task based on Bird's-Eye View (BEV) representation has drawn more and more attention, and BEV representation is promising as the foundation for next-generation…
BEVBert: Multimodal Map Pre-training for Language-guided Navigation
Dong An, Yuankai Qi, Yangguang Li +4
Large-scale pre-training has shown promising results on the vision-and-language navigation (VLN) task. However, most existing pre-training methods employ discrete panoramas to lear…
Neighbor Regularized Bayesian Optimization for Hyperparameter Optimization
Lei Cui, Yangguang Li, Xin Lu +2
Bayesian Optimization (BO) is a common solution to search optimal hyperparameters based on sample observations of a machine learning model. Existing BO algorithms could converge sl…
Towards Accurate Binary Neural Networks via Modeling Contextual Dependencies
Xingrun Xing, Yangguang Li, Wei Li +6
Existing Binary Neural Networks (BNNs) mainly operate on local convolutions with binarization function. However, such simple bit operations lack the ability of modeling contextual…
Task-Balanced Distillation for Object Detection
Ruining Tang, Zhenyu Liu, Yangguang Li +6
Mainstream object detectors are commonly constituted of two sub-tasks, including classification and regression tasks, implemented by two parallel heads. This classic design paradig…
1st Place Solutions for RxR-Habitat Vision-and-Language Navigation Competition (CVPR 2022)
Dong An, Zun Wang, Yangguang Li +5
This report presents the methods of the winning entry of the RxR-Habitat Competition in CVPR 2022. The competition addresses the problem of Vision-and-Language Navigation in Contin…
SupMAE: Supervised Masked Autoencoders Are Efficient Vision Learners
Feng Liang, Yangguang Li, Diana Marculescu
Recently, self-supervised Masked Autoencoders (MAE) have attracted unprecedented attention for their impressive representation learning ability. However, the pretext task, Masked I…
Democratizing Contrastive Language-Image Pre-training: A CLIP Benchmark of Data, Model, and Supervision
Yufeng Cui, Lichen Zhao, Feng Liang +2
Contrastive Language-Image Pretraining (CLIP) has emerged as a novel paradigm to learn visual models from language supervision. While researchers continue to push the frontier of C…
Rethinking the Zigzag Flattening for Image Reading
Qingsong Zhao, Yi Wang, Zhipeng Zhou +4
Sequence ordering of word vector matters a lot to text reading, which has been proven in natural language processing (NLP). However, the rule of different sequence ordering in comp…
RePre: Improving Self-Supervised Vision Transformer with Reconstructive Pre-training
Luya Wang, Feng Liang, Yangguang Li +3
Recently, self-supervised vision transformers have attracted unprecedented attention for their impressive representation learning ability. However, the dominant method, contrastive…
INTERN: A New Learning Paradigm Towards General Vision
Jing Shao, Siyu Chen, Yangguang Li +24
Enormous waves of technological innovations over the past several years, marked by the advances in AI technologies, are profoundly reshaping the industry and the society. However,…
Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm
Yangguang Li, Feng Liang, Lichen Zhao +5
Recently, large-scale Contrastive Language-Image Pre-training (CLIP) has attracted unprecedented attention for its impressive zero-shot recognition ability and excellent transferab…