45 citations · 120 across the 21 of their papers we have counts for
20 papers · 1 filter
Learning Shared RGB-D Fields: Unified Self-supervised Pre-training for Label-efficient LiDAR-Camera 3D Perception
Xiaohao Xu, Ye Li, Tianyi Zhang +3
Constructing large-scale labeled datasets for multi-modal perception model training in autonomous driving presents significant challenges. This has motivated the development of sel…
Vary: Scaling up the Vision Vocabulary for Large Vision-Language Models
Haoran Wei, Lingyu Kong, Jinyue Chen +6
Modern Large Vision-Language Models (LVLMs) enjoy the same vision vocabulary -- CLIP, which can cover most common vision tasks. However, for some special vision task that needs den…
Merlin:Empowering Multimodal LLMs with Foresight Minds
En Yu, Liang Zhao, Yana Wei +8
Humans possess the remarkable ability to foresee the future to a certain extent based on present observations, a skill we term as foresight minds. However, this capability remains…
DreamLLM: Synergistic Multimodal Comprehension and Creation
Runpei Dong, Chunrui Han, Yuang Peng +11
This paper presents DreamLLM, a learning framework that first achieves versatile Multimodal Large Language Models (MLLMs) empowered with frequently overlooked synergy between multi…
GroupLane: End-to-End 3D Lane Detection with Channel-wise Grouping
Zhuoling Li, Chunrui Han, Zheng Ge +5
Efficiency is quite important for 3D lane detection due to practical deployment demand. In this work, we propose a simple, fast, and end-to-end detector that still maintains high d…
GMM: Delving into Gradient Aware and Model Perceive Depth Mining for Monocular 3D Detection
Weixin Mao, Jinrong Yang, Zheng Ge +5
Depth perception is a crucial component of monoc-ular 3D detection tasks that typically involve ill-posed problems. In light of the success of sample mining techniques in 2D object…
BEVStereo++: Accurate Depth Estimation in Multi-view 3D Object Detection via Dynamic Temporal Stereo
Yinhao Li, Jinrong Yang, Jianjian Sun +3
Bounded by the inherent ambiguity of depth perception, contemporary multi-view 3D object detection methods fall into the performance bottleneck. Intuitively, leveraging temporal mu…
Exploring Recurrent Long-term Temporal Fusion for Multi-view 3D Perception
Chunrui Han, Jinrong Yang, Jianjian Sun +6
Long-term temporal fusion is a crucial but often overlooked technique in camera-based Bird's-Eye-View (BEV) 3D perception. Existing methods are mostly in a parallel manner. While p…
Towards 3D Object Detection with 2D Supervision
Jinrong Yang, Tiancai Wang, Zheng Ge +3
The great progress of 3D object detectors relies on large-scale data and 3D annotations. The annotation cost for 3D bounding boxes is extremely expensive while the 2D ones are easi…
Implicit and Efficient Point Cloud Completion for 3D Single Object Tracking
Pan Wang, Liangliang Ren, Shengkai Wu +4
The point cloud based 3D single object tracking has drawn increasing attention. Although many breakthroughs have been achieved, we also reveal two severe issues. By extensive analy…
Quality Matters: Embracing Quality Clues for Robust 3D Multi-Object Tracking
Jinrong Yang, En Yu, Zeming Li +2
3D Multi-Object Tracking (MOT) has achieved tremendous achievement thanks to the rapid development of 3D object detection and 2D MOT. Recent advanced works generally employ a serie…
StreamYOLO: Real-time Object Detection for Streaming Perception
Jinrong Yang, Songtao Liu, Zeming Li +2
The perceptive models of autonomous driving require fast inference within a low latency for safety. While existing works ignore the inevitable environmental changes after processin…
DBQ-SSD: Dynamic Ball Query for Efficient 3D Object Detection
Jinrong Yang, Lin Song, Songtao Liu +6
Many point-based 3D detectors adopt point-feature sampling strategies to drop some points for efficient inference. These strategies are typically based on fixed and handcrafted rul…
A Semantic Consistency Feature Alignment Object Detection Model Based on Mixed-Class Distribution Metrics
Lijun Gou, Jinrong Yang, Hangcheng Yu +3
Unsupervised domain adaptation is critical in various computer vision tasks, such as object detection, instance segmentation, etc. They attempt to reduce domain bias-induced perfor…
BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detection
Yinhao Li, Zheng Ge, Guanyi Yu +5
In this research, we propose a new 3D object detector with a trustworthy depth estimation, dubbed BEVDepth, for camera-based Bird's-Eye-View (BEV) 3D object detection. Our work is…
Real-time Object Detection for Streaming Perception
Jinrong Yang, Songtao Liu, Zeming Li +2
Autonomous driving requires the model to perceive the environment and (re)act within a low latency for safety. While past works ignore the inevitable changes in the environment aft…
Rectifying the Shortcut Learning of Background for Few-Shot Learning
Xu Luo, Longhui Wei, Liangjian Wen +4
The category gap between training and evaluation has been characterised as one of the main obstacles to the success of Few-Shot Learning (FSL). In this paper, we for the first time…
Carton dataset synthesis method for domain shift based on foreground texture decoupling and replacement
Lijun Gou, Shengkai Wu, Jinrong Yang +4
One major impediment in rapidly deploying object detection models for industrial applications is the lack of large annotated datasets. We currently have presented the Sacked Carton…
Gaussian Guided IoU: A Better Metric for Balanced Learning on Object Detection
Shengkai Wu, Jinrong Yang, Hangcheng Yu +2
For most of the anchor-based detectors, Intersection over Union(IoU) is widely utilized to assign targets for the anchors during training. However, IoU pays insufficient attention…
SCD: A Stacked Carton Dataset for Detection and Segmentation
Jinrong Yang, Shengkai Wu, Lijun Gou +5
Carton detection is an important technique in the automatic logistics system and can be applied to many applications such as the stacking and unstacking of cartons, the unloading o…