42 citations · 197 across the 18 of their papers we have counts for
18 papers
CoGen: 3D Consistent Video Generation via Adaptive Conditioning for Autonomous Driving
Yishen Ji, Ziyue Zhu, Zhenxin Zhu +7
Recent progress in driving video generation has shown significant potential for enhancing self-driving systems by providing scalable and controllable training data. Although pretra…
Eagle 2: Building Post-Training Data Strategies from Scratch for Frontier Vision-Language Models
Zhiqi Li, Guo Chen, Shilong Liu +24
Recently, promising progress has been made by open-source vision-language models (VLMs) in bringing their capabilities closer to those of proprietary frontier models. However, most…
ImagineMap: Enhanced HD Map Construction with SD Maps
Yishen Ji, Zhiqi Li, Tong Lu
Track Mapless demands models to process multi-view images and Standard-Definition (SD) maps, outputting lane and traffic element perceptions along with their topological relationsh…
Driving with InternVL: Oustanding Champion in the Track on Driving with Language of the Autonomous Grand Challenge at CVPR 2024
Jiahan Li, Zhiqi Li, Tong Lu
This technical report describes the methods we employed for the Driving with Language track of the CVPR 2024 Autonomous Grand Challenge. We utilized a powerful open-source multimod…
Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation
Zhenxin Li, Kailin Li, Shihao Wang +9
We propose Hydra-MDP, a novel paradigm employing multiple teachers in a teacher-student model. This approach uses knowledge distillation from both human and rule-based teachers to…
Video Mamba Suite: State Space Model as a Versatile Alternative for Video Understanding
Guo Chen, Yifei Huang, Jilan Xu +7
Understanding videos is one of the fundamental directions in computer vision research, with extensive efforts dedicated to exploring various architectures such as RNN, 3D CNN, and…
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…
DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Driving
Erfei Cui, Wenhai Wang, Zhiqi Li +7
Large language models (LLMs) have opened up new possibilities for intelligent agents, endowing them with human-like thinking and cognitive abilities. In this work, we delve into th…
Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?
Zhiqi Li, Zhiding Yu, Shiyi Lan +4
End-to-end autonomous driving recently emerged as a promising research direction to target autonomy from a full-stack perspective. Along this line, many of the latest works follow…
Swift Parameter-free Attention Network for Efficient Super-Resolution
Cheng Wan, Hongyuan Yu, Zhiqi Li +5
Single Image Super-Resolution (SISR) is a crucial task in low-level computer vision, aiming to reconstruct high-resolution images from low-resolution counterparts. Conventional att…
Leveraging Vision-Centric Multi-Modal Expertise for 3D Object Detection
Linyan Huang, Zhiqi Li, Chonghao Sima +4
Current research is primarily dedicated to advancing the accuracy of camera-only 3D object detectors (apprentice) through the knowledge transferred from LiDAR- or multi-modal-based…
FB-BEV: BEV Representation from Forward-Backward View Transformations
Zhiqi Li, Zhiding Yu, Wenhai Wang +3
View Transformation Module (VTM), where transformations happen between multi-view image features and Bird-Eye-View (BEV) representation, is a crucial step in camera-based BEV perce…
FB-OCC: 3D Occupancy Prediction based on Forward-Backward View Transformation
Zhiqi Li, Zhiding Yu, David Austin +4
This technical report summarizes the winning solution for the 3D Occupancy Prediction Challenge, which is held in conjunction with the CVPR 2023 Workshop on End-to-End Autonomous D…
InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions
Wenhai Wang, Jifeng Dai, Zhe Chen +9
Compared to the great progress of large-scale vision transformers (ViTs) in recent years, large-scale models based on convolutional neural networks (CNNs) are still in an early sta…
Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipe
Hongyang Li, Chonghao Sima, Jifeng Dai +19
Learning powerful representations in bird's-eye-view (BEV) for perception tasks is trending and drawing extensive attention both from industry and academia. Conventional approaches…
BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers
Zhiqi Li, Wenhai Wang, Hongyang Li +5
3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new f…
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers
Zhiqi Li, Wenhai Wang, Enze Xie +5
Panoptic segmentation involves a combination of joint semantic segmentation and instance segmentation, where image contents are divided into two types: things and stuff. We present…
An Introduction of mini-AlphaStar
Ruo-Ze Liu, Wenhai Wang, Yanjie Shen +3
StarCraft II (SC2) is a real-time strategy game in which players produce and control multiple units to fight against opponent's units. Due to its difficulties, such as huge state s…