1.4k citations · 3.6k across the 125 of their papers we have counts for
128 papers
FlowTurbo: Towards Real-time Flow-Based Image Generation with Velocity Refiner
Wenliang Zhao, Minglei Shi, Xumin Yu +2
Building on the success of diffusion models in visual generation, flow-based models reemerge as another prominent family of generative models that have achieved competitive or bett…
DC-Solver: Improving Predictor-Corrector Diffusion Sampler via Dynamic Compensation
Wenliang Zhao, Haolin Wang, Jie Zhou +1
Diffusion probabilistic models (DPMs) have shown remarkable performance in visual synthesis but are computationally expensive due to the need for multiple evaluations during the sa…
LOGO: A Long-Form Video Dataset for Group Action Quality Assessment
Shiyi Zhang, Wenxun Dai, Sujia Wang +4
Action quality assessment (AQA) has become an emerging topic since it can be extensively applied in numerous scenarios. However, most existing methods and datasets focus on single-…
Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models
Zuyan Liu, Yuhao Dong, Yongming Rao +2
In the realm of vision-language understanding, the proficiency of models in interpreting and reasoning over visual content has become a cornerstone for numerous applications. Howev…
SelfOcc: Self-Supervised Vision-Based 3D Occupancy Prediction
Yuanhui Huang, Wenzhao Zheng, Borui Zhang +2
3D occupancy prediction is an important task for the robustness of vision-centric autonomous driving, which aims to predict whether each point is occupied in the surrounding 3D spa…
Fast Shapley Value Estimation: A Unified Approach
Borui Zhang, Baotong Tian, Wenzhao Zheng +2
Shapley values have emerged as a widely accepted and trustworthy tool, grounded in theoretical axioms, for addressing challenges posed by black-box models like deep neural networks…
TCOVIS: Temporally Consistent Online Video Instance Segmentation
Junlong Li, Bingyao Yu, Yongming Rao +2
In recent years, significant progress has been made in video instance segmentation (VIS), with many offline and online methods achieving state-of-the-art performance. While offline…
Introspective Deep Metric Learning
Chengkun Wang, Wenzhao Zheng, Zheng Zhu +2
This paper proposes an introspective deep metric learning (IDML) framework for uncertainty-aware comparisons of images. Conventional deep metric learning methods focus on learning…
PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction
Sicheng Zuo, Wenzhao Zheng, Yuanhui Huang +2
Semantic segmentation in autonomous driving has been undergoing an evolution from sparse point segmentation to dense voxel segmentation, where the objective is to predict the seman…
Embodied Task Planning with Large Language Models
Zhenyu Wu, Ziwei Wang, Xiuwei Xu +2
Equipping embodied agents with commonsense is important for robots to successfully complete complex human instructions in general environments. Recent large language models (LLM) c…
Take-A-Photo: 3D-to-2D Generative Pre-training of Point Cloud Models
Ziyi Wang, Xumin Yu, Yongming Rao +2
With the overwhelming trend of mask image modeling led by MAE, generative pre-training has shown a remarkable potential to boost the performance of fundamental models in 2D vision.…
Towards Accurate Post-training Quantization for Diffusion Models
Changyuan Wang, Ziwei Wang, Xiuwei Xu +3
In this paper, we propose an accurate data-free post-training quantization framework of diffusion models (ADP-DM) for efficient image generation. Conventional data-free quantizatio…
3D Small Object Detection with Dynamic Spatial Pruning
Xiuwei Xu, Zhihao Sun, Ziwei Wang +3
In this paper, we propose an efficient feature pruning strategy for 3D small object detection. Conventional 3D object detection methods struggle on small objects due to the weak ge…
Dense Hybrid Proposal Modulation for Lane Detection
Yuejian Wu, Linqing Zhao, Jiwen Lu +1
In this paper, we present a dense hybrid proposal modulation (DHPM) method for lane detection. Most existing methods perform sparse supervision on a subset of high-scoring proposal…
LRRNet: A Novel Representation Learning Guided Fusion Network for Infrared and Visible Images
Hui Li, Tianyang Xu, Xiao-Jun Wu +2
Deep learning based fusion methods have been achieving promising performance in image fusion tasks. This is attributed to the network architecture that plays a very important role…
Learning Accurate Performance Predictors for Ultrafast Automated Model Compression
Ziwei Wang, Jiwen Lu, Han Xiao +2
In this paper, we propose an ultrafast automated model compression framework called SeerNet for flexible network deployment. Conventional non-differen-tiable methods discretely sea…
Binarizing Sparse Convolutional Networks for Efficient Point Cloud Analysis
Xiuwei Xu, Ziwei Wang, Jie Zhou +1
In this paper, we propose binary sparse convolutional networks called BSC-Net for efficient point cloud analysis. We empirically observe that sparse convolution operation causes la…
Efficient Meshy Neural Fields for Animatable Human Avatars
Xiaoke Huang, Yiji Cheng, Yansong Tang +3
Efficiently digitizing high-fidelity animatable human avatars from videos is a challenging and active research topic. Recent volume rendering-based neural representations open a ne…
OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perception
Xiaofeng Wang, Zheng Zhu, Wenbo Xu +7
Semantic occupancy perception is essential for autonomous driving, as automated vehicles require a fine-grained perception of the 3D urban structures. However, existing relevant be…
Unleashing Text-to-Image Diffusion Models for Visual Perception
Wenliang Zhao, Yongming Rao, Zuyan Liu +3
Diffusion models (DMs) have become the new trend of generative models and have demonstrated a powerful ability of conditional synthesis. Among those, text-to-image diffusion models…
Tri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction
Yuanhui Huang, Wenzhao Zheng, Yunpeng Zhang +2
Modern methods for vision-centric autonomous driving perception widely adopt the bird's-eye-view (BEV) representation to describe a 3D scene. Despite its better efficiency than vox…
SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Driving
Yi Wei, Linqing Zhao, Wenzhao Zheng +3
3D scene understanding plays a vital role in vision-based autonomous driving. While most existing methods focus on 3D object detection, they have difficulty describing real-world o…
Category-level Shape Estimation for Densely Cluttered Objects
Zhenyu Wu, Ziwei Wang, Jiwen Lu +1
Accurately estimating the shape of objects in dense clutters makes important contribution to robotic packing, because the optimal object arrangement requires the robot planner to a…
UniPC: A Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models
Wenliang Zhao, Lujia Bai, Yongming Rao +2
Diffusion probabilistic models (DPMs) have demonstrated a very promising ability in high-resolution image synthesis. However, sampling from a pre-trained DPM is time-consuming due…