no code implementations • 17 Sep 2024 • Jianxiong Gao, Yuqian Fu, Yun Wang, Xuelin Qian, Jianfeng Feng, Yanwei Fu
To advance this task, we present the fMRI-3D dataset, which includes data from 15 participants and showcases a total of 4768 3D objects.
1 code implementation • 24 May 2024 • Yuankun Yang, Li Zhang, Ziyang Xie, Zhiyuan Yuan, Jianfeng Feng, Xiatian Zhu, Yu-Gang Jiang
Conceptually, we reformulate this task as a {\em fMRI conditioned 3D object generation} problem.
no code implementations • 16 Apr 2024 • Zhichao Zhu, Yang Qi, Wenlian Lu, Zhigang Wang, Lu Cao, Jianfeng Feng
The energy-efficient and brain-like information processing abilities of Spiking Neural Networks (SNNs) have attracted considerable attention, establishing them as a crucial element of brain-inspired computing.
no code implementations • 27 Mar 2024 • Jingyang Huo, Yikai Wang, Xuelin Qian, Yun Wang, Chong Li, Jianfeng Feng, Yanwei Fu
Recent fMRI-to-image approaches mainly focused on associating fMRI signals with specific conditions of pre-trained diffusion models.
no code implementations • 18 Mar 2024 • Haochen Jiang, Yueming Xu, Yihan Zeng, Hang Xu, Wei zhang, Jianfeng Feng, Li Zhang
We model the geometric structure of the scene with occupancy representation and distill the pre-trained open vocabulary model into a 3D language field via volume rendering for zero-shot inference.
no code implementations • 17 Mar 2024 • Cenyuan Zhang, Xiaoqing Zheng, Ruicheng Yin, Shujie Geng, Jianhan Xu, Xuan Gao, Changze Lv, Zixuan Ling, Xuanjing Huang, Miao Cao, Jianfeng Feng
Deciphering natural language from brain activity through non-invasive devices remains a formidable challenge.
1 code implementation • 13 Mar 2024 • Hengyuan Ma, Wenlian Lu, Jianfeng Feng
Combinatorial optimization problems are widespread but inherently challenging due to their discrete nature.
no code implementations • 4 Jan 2024 • Xinzhe Luo, Xin Wang, Linda Shapiro, Chun Yuan, Jianfeng Feng, Xiahai Zhuang
We propose a novel hierarchical variational auto-encoding architecture to realise the inference procedure of the latent variables, where the registration parameters can be explicitly estimated in a mathematically interpretable fashion.
1 code implementation • 1 Jan 2024 • Zhichao Zhu, Yang Qi, Wenlian Lu, Jianfeng Feng
Sensory perception originates from the responses of sensory neurons, which react to a collection of sensory signals linked to various physical attributes of a singular perceptual object.
no code implementations • 12 Dec 2023 • Jianxiong Gao, Yuqian Fu, Yun Wang, Xuelin Qian, Jianfeng Feng, Yanwei Fu
In this paper, we introduce Recon3DMind, an innovative task aimed at reconstructing 3D visuals from Functional Magnetic Resonance Imaging (fMRI) signals, marking a significant advancement in the fields of cognitive neuroscience and computer vision.
no code implementations • 21 Nov 2023 • Ziqi Yu, Botao Zhao, Shengjie Zhang, Xiang Chen, Jianfeng Feng, Tingying Peng, Xiao-Yong Zhang
To address these issues, we introduce hierarchical granularity discrimination, which exploits various levels of semantic information present in medical images.
no code implementations • 1 Nov 2023 • Xuelin Qian, Yun Wang, Jingyang Huo, Jianfeng Feng, Yanwei Fu
The exploration of brain activity and its decoding from fMRI data has been a longstanding pursuit, driven by its potential applications in brain-computer interfaces, medical diagnostics, and virtual reality.
no code implementations • 2 Aug 2023 • Wenlian Lu, Longbin Zeng, Xin Du, Wenyong Zhang, Shitong Xiang, Huarui Wang, Jiexiang Wang, Mingda Ji, Yubo Hou, Minglong Wang, Yuhao Liu, Zhongyu Chen, Qibao Zheng, Ningsheng Xu, Jianfeng Feng
In comparison to most brain simulations with a homogeneous global structure, we highlight that the sparseness, couplingness and heterogeneity in the sMRI, DTI and PET data of the brain has an essential impact on the efficiency of brain simulation, which is proved from the scaling experiments that the DTB of human brain simulation is communication-intensive and memory-access intensive computing systems rather than computation-intensive.
1 code implementation • 30 May 2023 • Hengyuan Ma, Yang Qi, Li Zhang, Wenlian Lu, Jianfeng Feng
Building robust, interpretable, and secure AI system requires quantifying and representing uncertainty under a probabilistic perspective to mimic human cognitive abilities.
2 code implementations • 23 May 2023 • Yang Qi, Zhichao Zhu, Yiming Wei, Lu Cao, Zhigang Wang, Jie Zhang, Wenlian Lu, Jianfeng Feng
To account for the propagation of correlated neural variability, we derive from first principles a moment embedding for spiking neural network (SNN).
no code implementations • 26 Mar 2023 • Xuelin Qian, Yikai Wang, Yanwei Fu, Xinwei Sun, xiangyang xue, Jianfeng Feng
Our Latent Embedding Alignment (LEA) model concurrently recovers visual stimuli from fMRI signals and predicts brain activity from images within a unified framework.
1 code implementation • 13 Feb 2023 • Hengyuan Ma, Li Zhang, Xiatian Zhu, Jianfeng Feng
Compared with the latest generative models (\eg, CLD-SGM, DDIM, and Analytic-DDIM), PDS can achieve the best sampling quality on CIFAR-10 at a FID score of 1. 99.
no code implementations • 15 Jan 2023 • Jiayi Han, Longbin Zeng, Liang Du, Weiyang Ding, Jianfeng Feng
In this work, we propose a novel complementary learning approach to enhance test-time adaptation (TTA), which has been proven to exhibit good performance on testing data with distribution shifts such as corruptions.
no code implementations • 4 Dec 2022 • Ziqi Yu, Xiaoyang Han, Shengjie Zhang, Jianfeng Feng, Tingying Peng, Xiao-Yong Zhang
Our results demonstrate that MouseGAN++, as a simultaneous image synthesis and segmentation method, can be used to fuse cross-modality information in an unpaired manner and yield more robust performance in the absence of multimodal data.
no code implementations • 29 Nov 2022 • Wenlian Lu, Xin Du, Jiexiang Wang, Longbin Zeng, Leijun Ye, Shitong Xiang, Qibao Zheng, Jie Zhang, Ningsheng Xu, Jianfeng Feng
Here, we present the Digital Brain (DB), a platform for simulating spiking neuronal networks at the large neuron scale of the human brain based on personalized magnetic-resonance-imaging data and biological constraints.
no code implementations • 24 Aug 2022 • Liang Du, Xiaoqing Ye, Xiao Tan, Edward Johns, Bo Chen, Errui Ding, xiangyang xue, Jianfeng Feng
A feasible method is investigated to construct conceptual scenes without external datasets.
3 code implementations • 19 Jul 2022 • Li Zhang, Jiachen Lu, Sixiao Zheng, Xinxuan Zhao, Xiatian Zhu, Yanwei Fu, Tao Xiang, Jianfeng Feng, Philip H. S. Torr
Extensive experiments show that our methods achieve appealing performance on a variety of dense prediction tasks (e. g., object detection and instance segmentation and semantic segmentation) as well as image classification.
1 code implementation • 5 Jul 2022 • Jiachen Lu, Junge Zhang, Xiatian Zhu, Jianfeng Feng, Tao Xiang, Li Zhang
With linear complexity, much longer token sequences are permitted by SOFT, resulting in superior trade-off between accuracy and complexity.
1 code implementation • 5 Jul 2022 • Hengyuan Ma, Li Zhang, Xiatian Zhu, Jianfeng Feng
However, a fundamental limitation is that their inference is very slow due to a need for many (e. g., 2000) iterations of sequential computations.
no code implementations • 8 Jun 2022 • Hengyuan Ma, Li Zhang, Xiatian Zhu, Jingfeng Zhang, Jianfeng Feng
To ensure stability of convergence in sampling and generation quality, however, this sequential sampling process has to take a small step size and many sampling iterations (e. g., 2000).
1 code implementation • 20 Feb 2022 • Sixiao Zheng, Ke Fan, Yanxi Hou, Jianfeng Feng, Yanwei Fu
In contrast, the GPD fits the distribution of distance to the centroid exceeding a sufficiently large threshold, leading to a more stable performance of GPD k-means.
no code implementations • ICCV 2021 • Zhikang Zou, Xiaoqing Ye, Liang Du, Xianhui Cheng, Xiao Tan, Li Zhang, Jianfeng Feng, xiangyang xue, Errui Ding
Low-cost monocular 3D object detection plays a fundamental role in autonomous driving, whereas its accuracy is still far from satisfactory.
1 code implementation • 3 Dec 2021 • Zheyuan Zhou, Liang Du, Xiaoqing Ye, Zhikang Zou, Xiao Tan, Li Zhang, xiangyang xue, Jianfeng Feng
Monocular 3D object detection aims to predict the object location, dimension and orientation in 3D space alongside the object category given only a monocular image.
no code implementations • 29 Sep 2021 • Hengyuan Ma, Qi Yang, Bowen Sun, Long Shun, Junkui Li, Jianfeng Feng
Graph neural networks (GNN) demonstrate excellent performance on many graph-based tasks; however, they also impose a heavy computational burden when trained on a large-scale graph.
1 code implementation • CVPR 2021 • Li Wang, Liang Du, Xiaoqing Ye, Yanwei Fu, Guodong Guo, xiangyang xue, Jianfeng Feng, Li Zhang
The objective of this paper is to learn context- and depth-aware feature representation to solve the problem of monocular 3D object detection.
Ranked #13 on Monocular 3D Object Detection on KITTI Cars Moderate
1 code implementation • 5 Feb 2021 • Hanqing Chao, Kun Wang, Yiwei He, Junping Zhang, Jianfeng Feng
In this paper, we present a novel perspective that utilizes gait as a deep set, which means that a set of gait frames are integrated by a global-local fused deep network inspired by the way our left- and right-hemisphere processes information to learn information that can be used in identification.
5 code implementations • CVPR 2021 • Sixiao Zheng, Jiachen Lu, Hengshuang Zhao, Xiatian Zhu, Zekun Luo, Yabiao Wang, Yanwei Fu, Jianfeng Feng, Tao Xiang, Philip H. S. Torr, Li Zhang
In this paper, we aim to provide an alternative perspective by treating semantic segmentation as a sequence-to-sequence prediction task.
Ranked #2 on Semantic Segmentation on FoodSeg103 (using extra training data)
no code implementations • CVPR 2020 • Liang Du, Xiaoqing Ye, Xiao Tan, Jianfeng Feng, Zhenbo Xu, Errui Ding, Shilei Wen
Object detection from 3D point clouds remains a challenging task, though recent studies pushed the envelope with the deep learning techniques.
no code implementations • 1 Mar 2020 • Liang Du, Jingang Tan, xiangyang xue, Lili Chen, Hongkai Wen, Jianfeng Feng, Jiamao Li, Xiaolin Zhang
We propose a novel fast and robust 3D point clouds segmentation framework via coupled feature selection, named 3DCFS, that jointly performs semantic and instance segmentation.
1 code implementation • NeurIPS 2019 • Chenyang Tao, Liqun Chen, Shuyang Dai, Junya Chen, Ke Bai, Dong Wang, Jianfeng Feng, Wenlian Lu, Georgiy Bobashev, Lawrence Carin
Inference, estimation, sampling and likelihood evaluation are four primary goals of probabilistic modeling.
no code implementations • 25 Sep 2019 • Sixiao Zheng, Yanxi Hou, Yanwei Fu, Jianfeng Feng
We thus propose a novel algorithm called Extreme Value k-means (EV k-means), including GEV k-means and GPD k-means.
3 code implementations • 15 Nov 2018 • Hanqing Chao, Yiwei He, Junping Zhang, Jianfeng Feng
In this paper we present a novel perspective, where a gait is regarded as a set consisting of independent frames.
Ranked #2 on Multiview Gait Recognition on OU-MVLP
1 code implementation • ICML 2018 • Chenyang Tao, Liqun Chen, Ricardo Henao, Jianfeng Feng, Lawrence Carin Duke
To assess the difference between real and synthetic data, Generative Adversarial Networks (GANs) are trained using a distribution discrepancy measure.
no code implementations • CVPR 2018 • Changmao Cheng, Yanwei Fu, Yu-Gang Jiang, Wei Liu, Wenlian Lu, Jianfeng Feng, xiangyang xue
Inspired by the recent neuroscience studies on the left-right asymmetry of the human brain in processing low and high spatial frequency information, this paper introduces a dual skipping network which carries out coarse-to-fine object categorization.