1.4k citations · 3.6k across the 125 of their papers we have counts for
19 papers · 2 filters
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…
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…
AdaPoinTr: Diverse Point Cloud Completion with Adaptive Geometry-Aware Transformers
Xumin Yu, Yongming Rao, Ziyi Wang +2
In this paper, we present a new method that reformulates point cloud completion as a set-to-set translation problem and design a new model, called PoinTr, which adopts a Transforme…
DiffTalk: Crafting Diffusion Models for Generalized Audio-Driven Portraits Animation
Shuai Shen, Wenliang Zhao, Zibin Meng +4
Talking head synthesis is a promising approach for the video production industry. Recently, a lot of effort has been devoted in this research area to improve the generation quality…