37 citations · 98 across the 12 of their papers we have counts for
13 papers
UFO: A Unified Approach to Fine-grained Visual Perception via Open-ended Language Interface
Hao Tang, Chenwei Xie, Haiyang Wang +5
Generalist models have achieved remarkable success in both language and vision-language tasks, showcasing the potential of unified modeling. However, effectively integrating fine-g…
TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters
Haiyang Wang, Yue Fan, Muhammad Ferjad Naeem +5
Transformers have become the predominant architecture in foundation models due to their excellent performance across various domains. However, the substantial cost of scaling these…
GiT: Towards Generalist Vision Transformer through Universal Language Interface
Haiyang Wang, Hao Tang, Li Jiang +5
This paper proposes a simple, yet effective framework, called GiT, simultaneously applicable for various vision tasks only with a vanilla ViT. Motivated by the universality of the…
PRED: Pre-training via Semantic Rendering on LiDAR Point Clouds
Hao Yang, Haiyang Wang, Di Dai +1
Pre-training is crucial in 3D-related fields such as autonomous driving where point cloud annotation is costly and challenging. Many recent studies on point cloud pre-training, how…
UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View Representation
Haiyang Wang, Hao Tang, Shaoshuai Shi +4
Jointly processing information from multiple sensors is crucial to achieving accurate and robust perception for reliable autonomous driving systems. However, current 3D perception…
DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets
Haiyang Wang, Chen Shi, Shaoshuai Shi +5
Designing an efficient yet deployment-friendly 3D backbone to handle sparse point clouds is a fundamental problem in 3D perception. Compared with the customized sparse convolution,…
CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds
Haiyang Wang, Lihe Ding, Shaocong Dong +5
We present a novel two-stage fully sparse convolutional 3D object detection framework, named CAGroup3D. Our proposed method first generates some high-quality 3D proposals by levera…
RBGNet: Ray-based Grouping for 3D Object Detection
Haiyang Wang, Shaoshuai Shi, Ze Yang +5
As a fundamental problem in computer vision, 3D object detection is experiencing rapid growth. To extract the point-wise features from the irregularly and sparsely distributed poin…
Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis
Jikai Jin, Bohang Zhang, Haiyang Wang +1
Distributionally robust optimization (DRO) is a widely-used approach to learn models that are robust against distribution shift. Compared with the standard optimization setting, th…
Collaborative Visual Navigation
Haiyang Wang, Wenguan Wang, Xizhou Zhu +2
As a fundamental problem for Artificial Intelligence, multi-agent system (MAS) is making rapid progress, mainly driven by multi-agent reinforcement learning (MARL) techniques. Howe…
Drug-Target Interaction Prediction with Graph Attention networks
Haiyang Wang, Guangyu Zhou, Siqi Liu +2
Motivation: Predicting Drug-Target Interaction (DTI) is a well-studied topic in bioinformatics due to its relevance in the fields of proteomics and pharmaceutical research. Althoug…
Explicit Shape Encoding for Real-Time Instance Segmentation
Wenqiang Xu, Haiyang Wang, Fubo Qi +1
In this paper, we propose a novel top-down instance segmentation framework based on explicit shape encoding, named \textbf{ESE-Seg}. It largely reduces the computational consumptio…
Visual Rhythm Prediction with Feature-Aligning Network
Yutong Xie, Haiyang Wang, Yan Hao +1
In this paper, we propose a data-driven visual rhythm prediction method, which overcomes the previous works' deficiency that predictions are made primarily by human-crafted hard ru…