63 citations · 181 across the 20 of their papers we have counts for
21 papers
Dita: Scaling Diffusion Transformer for Generalist Vision-Language-Action Policy
Zhi Hou, Tianyi Zhang, Yuwen Xiong +8
While recent vision-language-action models trained on diverse robot datasets exhibit promising generalization capabilities with limited in-domain data, their reliance on compact ac…
Diffusion Transformer Policy
Zhi Hou, Tianyi Zhang, Yuwen Xiong +6
Recent large vision-language-action models pretrained on diverse robot datasets have demonstrated the potential for generalizing to new environments with a few in-domain data. Howe…
Monocular Occupancy Prediction for Scalable Indoor Scenes
Hongxiao Yu, Yuqi Wang, Yuntao Chen +1
Camera-based 3D occupancy prediction has recently garnered increasing attention in outdoor driving scenes. However, research in indoor scenes remains relatively unexplored. The cor…
Enhancing End-to-End Autonomous Driving with Latent World Model
Yingyan Li, Lue Fan, Jiawei He +4
In autonomous driving, end-to-end planners directly utilize raw sensor data, enabling them to extract richer scene features and reduce information loss compared to traditional plan…
Continual Forgetting for Pre-trained Vision Models
Hongbo Zhao, Bolin Ni, Haochen Wang +6
For privacy and security concerns, the need to erase unwanted information from pre-trained vision models is becoming evident nowadays. In real-world scenarios, erasure requests ori…
Efficient Deformable ConvNets: Rethinking Dynamic and Sparse Operator for Vision Applications
Yuwen Xiong, Zhiqi Li, Yuntao Chen +10
We introduce Deformable Convolution v4 (DCNv4), a highly efficient and effective operator designed for a broad spectrum of vision applications. DCNv4 addresses the limitations of i…
MM-Interleaved: Interleaved Image-Text Generative Modeling via Multi-modal Feature Synchronizer
Changyao Tian, Xizhou Zhu, Yuwen Xiong +10
Developing generative models for interleaved image-text data has both research and practical value. It requires models to understand the interleaved sequences and subsequently gene…
Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Driving
Yuqi Wang, Jiawei He, Lue Fan +3
In autonomous driving, predicting future events in advance and evaluating the foreseeable risks empowers autonomous vehicles to better plan their actions, enhancing safety and effi…
PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentation
Yuqi Wang, Yuntao Chen, Xingyu Liao +2
Comprehensive modeling of the surrounding 3D world is key to the success of autonomous driving. However, existing perception tasks like object detection, road structure segmentatio…
Tracking Objects with 3D Representation from Videos
Jiawei He, Lue Fan, Yuqi Wang +4
Data association is a knotty problem for 2D Multiple Object Tracking due to the object occlusion. However, in 3D space, data association is not so hard. Only with a 3D Kalman Filte…
Weakly Supervised 3D Object Detection with Multi-Stage Generalization
Jiawei He, Yuqi Wang, Yuntao Chen +1
With the rapid development of large models, the need for data has become increasingly crucial. Especially in 3D object detection, costly manual annotations have hindered further ad…
Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memory
Xizhou Zhu, Yuntao Chen, Hao Tian +10
The captivating realm of Minecraft has attracted substantial research interest in recent years, serving as a rich platform for developing intelligent agents capable of functioning…
Real-Aug: Realistic Scene Synthesis for LiDAR Augmentation in 3D Object Detection
Jinglin Zhan, Tiejun Liu, Rengang Li +3
Data and model are the undoubtable two supporting pillars for LiDAR object detection. However, data-centric works have fallen far behind compared with the ever-growing list of fanc…
SheetCopilot: Bringing Software Productivity to the Next Level through Large Language Models
Hongxin Li, Jingran Su, Yuntao Chen +2
Computer end users have spent billions of hours completing daily tasks like tabular data processing and project timeline scheduling. Most of these tasks are repetitive and error-pr…
Once Detected, Never Lost: Surpassing Human Performance in Offline LiDAR based 3D Object Detection
Lue Fan, Yuxue Yang, Yiming Mao +4
This paper aims for high-performance offline LiDAR-based 3D object detection. We first observe that experienced human annotators annotate objects from a track-centric perspective.…
Fully Sparse Fusion for 3D Object Detection
Yingyan Li, Lue Fan, Yang Liu +4
Currently prevalent multimodal 3D detection methods are built upon LiDAR-based detectors that usually use dense Bird's-Eye-View (BEV) feature maps. However, the cost of such BEV fe…
3D Video Object Detection with Learnable Object-Centric Global Optimization
Jiawei He, Yuntao Chen, Naiyan Wang +1
We explore long-term temporal visual correspondence-based optimization for 3D video object detection in this work. Visual correspondence refers to one-to-one mappings for pixels ac…
FrustumFormer: Adaptive Instance-aware Resampling for Multi-view 3D Detection
Yuqi Wang, Yuntao Chen, Zhaoxiang Zhang
The transformation of features from 2D perspective space to 3D space is essential to multi-view 3D object detection. Recent approaches mainly focus on the design of view transforma…
GIFS: Neural Implicit Function for General Shape Representation
Jianglong Ye, Yuntao Chen, Naiyan Wang +1
Recent development of neural implicit function has shown tremendous success on high-quality 3D shape reconstruction. However, most works divide the space into inside and outside of…
Immortal Tracker: Tracklet Never Dies
Qitai Wang, Yuntao Chen, Ziqi Pang +2
Previous online 3D Multi-Object Tracking(3DMOT) methods terminate a tracklet when it is not associated with new detections for a few frames. But if an object just goes dark, like b…
Online Adaptation for Implicit Object Tracking and Shape Reconstruction in the Wild
Jianglong Ye, Yuntao Chen, Naiyan Wang +1
Tracking and reconstructing 3D objects from cluttered scenes are the key components for computer vision, robotics and autonomous driving systems. While recent progress in implicit…