Search Results for author: Zhiqi Li

Found 19 papers, 14 papers with code

Improving Group Connectivity for Generalization of Federated Deep Learning

no code implementations29 Feb 2024 Zexi Li, Jie Lin, Zhiqi Li, Didi Zhu, Chao Wu

Bridging the gap between LMC and FL, in this paper, we leverage fixed anchor models to empirically and theoretically study the transitivity property of connectivity from two models (LMC) to a group of models (model fusion in FL).

Federated Learning Linear Mode Connectivity

Training-time Neuron Alignment through Permutation Subspace for Improving Linear Mode Connectivity and Model Fusion

no code implementations2 Feb 2024 Zexi Li, Zhiqi Li, Jie Lin, Tao Shen, Tao Lin, Chao Wu

In deep learning, stochastic gradient descent often yields functionally similar yet widely scattered solutions in the weight space even under the same initialization, causing barriers in the Linear Mode Connectivity (LMC) landscape.

Federated Learning Linear Mode Connectivity

Efficient Deformable ConvNets: Rethinking Dynamic and Sparse Operator for Vision Applications

1 code implementation11 Jan 2024 Yuwen Xiong, Zhiqi Li, Yuntao Chen, Feng Wang, Xizhou Zhu, Jiapeng Luo, Wenhai Wang, Tong Lu, Hongsheng Li, Yu Qiao, Lewei Lu, Jie zhou, Jifeng Dai

The advancements in speed and efficiency of DCNv4, combined with its robust performance across diverse vision tasks, show its potential as a foundational building block for future vision models.

Image Classification Image Generation +1

Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?

1 code implementation5 Dec 2023 Zhiqi Li, Zhiding Yu, Shiyi Lan, Jiahan Li, Jan Kautz, Tong Lu, Jose M. Alvarez

We initially observed that the nuScenes dataset, characterized by relatively simple driving scenarios, leads to an under-utilization of perception information in end-to-end models incorporating ego status, such as the ego vehicle's velocity.

Autonomous Driving

ET3D: Efficient Text-to-3D Generation via Multi-View Distillation

no code implementations27 Nov 2023 Yiming Chen, Zhiqi Li, Peidong Liu

The main insight is that we exploit the images generated by a large pre-trained text-to-image diffusion model, to supervise the training of a text conditioned 3D generative adversarial network.

Generative Adversarial Network Text to 3D +1

Swift Parameter-free Attention Network for Efficient Super-Resolution

1 code implementation21 Nov 2023 Cheng Wan, Hongyuan Yu, Zhiqi Li, Yihang Chen, Yajun Zou, Yuqing Liu, Xuanwu Yin, Kunlong Zuo

To address this issue, we propose the Swift Parameter-free Attention Network (SPAN), a highly efficient SISR model that balances parameter count, inference speed, and image quality.

Image Super-Resolution

Leveraging Vision-Centric Multi-Modal Expertise for 3D Object Detection

1 code implementation NeurIPS 2023 Linyan Huang, Zhiqi Li, Chonghao Sima, Wenhai Wang, Jingdong Wang, Yu Qiao, Hongyang Li

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 counterparts (expert).

3D Object Detection object-detection

FB-OCC: 3D Occupancy Prediction based on Forward-Backward View Transformation

1 code implementation4 Jul 2023 Zhiqi Li, Zhiding Yu, David Austin, Mingsheng Fang, Shiyi Lan, Jan Kautz, Jose M. Alvarez

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 Driving and CVPR 23 Workshop on Vision-Centric Autonomous Driving Workshop.

Autonomous Driving Prediction Of Occupancy Grid Maps

RemoteTouch: Enhancing Immersive 3D Video Communication with Hand Touch

no code implementations28 Feb 2023 Yizhong Zhang, Zhiqi Li, Sicheng Xu, Chong Li, Jiaolong Yang, Xin Tong, Baining Guo

A key challenge in emulating the remote hand touch is the realistic rendering of the participant's hand and arm as the hand touches the screen.

InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions

2 code implementations CVPR 2023 Wenhai Wang, Jifeng Dai, Zhe Chen, Zhenhang Huang, Zhiqi Li, Xizhou Zhu, Xiaowei Hu, Tong Lu, Lewei Lu, Hongsheng Li, Xiaogang Wang, Yu Qiao

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 state.

 Ranked #1 on Instance Segmentation on COCO test-dev (AP50 metric, using extra training data)

Classification Image Classification +3

Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipe

2 code implementations12 Sep 2022 Hongyang Li, Chonghao Sima, Jifeng Dai, Wenhai Wang, Lewei Lu, Huijie Wang, Jia Zeng, Zhiqi Li, Jiazhi Yang, Hanming Deng, Hao Tian, Enze Xie, Jiangwei Xie, Li Chen, Tianyu Li, Yang Li, Yulu Gao, Xiaosong Jia, Si Liu, Jianping Shi, Dahua Lin, Yu Qiao

As sensor configurations get more complex, integrating multi-source information from different sensors and representing features in a unified view come of vital importance.

Autonomous Driving

Federated Learning with Label Distribution Skew via Logits Calibration

2 code implementations1 Sep 2022 Jie Zhang, Zhiqi Li, Bo Li, Jianghe Xu, Shuang Wu, Shouhong Ding, Chao Wu

Extensive experiments on federated datasets and real-world datasets demonstrate that FedLC leads to a more accurate global model and much improved performance.

Federated Learning

BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers

3 code implementations31 Mar 2022 Zhiqi Li, Wenhai Wang, Hongyang Li, Enze Xie, Chonghao Sima, Tong Lu, Qiao Yu, Jifeng Dai

In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV queries.

3D Object Detection Autonomous Driving +1

An Introduction of mini-AlphaStar

1 code implementation14 Apr 2021 Ruo-Ze Liu, Wenhai Wang, Yanjie Shen, Zhiqi Li, Yang Yu, Tong Lu

StarCraft II (SC2) is a real-time strategy game in which players produce and control multiple units to fight against opponent's units.

Starcraft Starcraft II

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