b'Yonghong Tian'

research

∙ 08/14/2023

Knowledge Prompt-tuning for Sequential Recommendation

Pre-trained language models (PLMs) have demonstrated strong performance ...

0 Jianyang Zhai, et al. ∙

research

∙ 08/08/2023

SSTFormer: Bridging Spiking Neural Network and Memory Support Transformer for Frame-Event based Recognition

Event camera-based pattern recognition is a newly arising research topic...

0 Xiao Wang, et al. ∙

research

∙ 08/08/2023

SODFormer: Streaming Object Detection with Transformer Using Events and Frames

DAVIS camera, streaming two complementary sensing modalities of asynchro...

0 Dianze Li, et al. ∙

research

∙ 07/14/2023

Learning Sparse Neural Networks with Identity Layers

The sparsity of Deep Neural Networks is well investigated to maximize th...

0 Mingjian Ni, et al. ∙

research

∙ 07/04/2023

Spike-driven Transformer

Spiking Neural Networks (SNNs) provide an energy-efficient deep learning...

0 Man Yao, et al. ∙

research

∙ 06/08/2023

Point-Voxel Absorbing Graph Representation Learning for Event Stream based Recognition

Sampled point and voxel methods are usually employed to downsample the d...

4 Bo Jiang, et al. ∙

research

∙ 06/08/2023

Population-Based Evolutionary Gaming for Unsupervised Person Re-identification

Unsupervised person re-identification has achieved great success through...

0 Yunpeng Zhai, et al. ∙

research

∙ 06/02/2023

Deep recurrent spiking neural networks capture both static and dynamic representations of the visual cortex under movie stimuli

In the real world, visual stimuli received by the biological visual syst...

0 Liwei Huang, et al. ∙

research

∙ 06/01/2023

Auto-Spikformer: Spikformer Architecture Search

The integration of self-attention mechanisms into Spiking Neural Network...

0 Kaiwei Che, et al. ∙

research

∙ 05/23/2023

Temporal Contrastive Learning for Spiking Neural Networks

Biologically inspired spiking neural networks (SNNs) have garnered consi...

0 Haonan Qiu, et al. ∙

research

∙ 05/22/2023

Album Storytelling with Iterative Story-aware Captioning and Large Language Models

This work studies how to transform an album to vivid and coherent storie...

0 Munan Ning, et al. ∙

research

∙ 05/20/2023

Probabilistic Modeling: Proving the Lottery Ticket Hypothesis in Spiking Neural Network

The Lottery Ticket Hypothesis (LTH) states that a randomly-initialized l...

0 Man Yao, et al. ∙

research

∙ 05/10/2023

Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation

Deep spiking neural networks (SNNs) have drawn much attention in recent ...

0 Chenlin Zhou, et al. ∙

research

∙ 04/25/2023

Parallel Spiking Neurons with High Efficiency and Ability to Learn Long-term Dependencies

Vanilla spiking neurons in Spiking Neural Networks (SNNs) use charge-fir...

0 Wei Fang, et al. ∙

research

∙ 04/24/2023

Spikingformer: Spike-driven Residual Learning for Transformer-based Spiking Neural Network

Spiking neural networks (SNNs) offer a promising energy-efficient altern...

0 Chenlin Zhou, et al. ∙

research

∙ 04/21/2023

Picking Up Quantization Steps for Compressed Image Classification

The sensitivity of deep neural networks to compressed images hinders the...

0 Li Ma, et al. ∙

research

∙ 04/02/2023

Learning with Fantasy: Semantic-Aware Virtual Contrastive Constraint for Few-Shot Class-Incremental Learning

Few-shot class-incremental learning (FSCIL) aims at learning to classify...

0 Zeyin Song, et al. ∙

research

∙ 03/09/2023

Deep Spiking Neural Networks with High Representation Similarity Model Visual Pathways of Macaque and Mouse

Deep artificial neural networks (ANNs) play a major role in modeling the...

0 Liwei Huang, et al. ∙

research

∙ 02/25/2023

A Unified Framework for Soft Threshold Pruning

Soft threshold pruning is among the cutting-edge pruning methods with st...

0 Yanqi Chen, et al. ∙

research

∙ 02/20/2023

Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey

With the urgent demand for generalized deep models, many pre-trained big...

1 Xiao Wang, et al. ∙

research

∙ 01/27/2023

Training Full Spike Neural Networks via Auxiliary Accumulation Pathway

Due to the binary spike signals making converting the traditional high-p...

0 Guangyao Chen, et al. ∙

research

∙ 01/18/2023

MADAv2: Advanced Multi-Anchor Based Active Domain Adaptation Segmentation

Unsupervised domain adaption has been widely adopted in tasks with scarc...

0 Munan Ning, et al. ∙

research

∙ 12/28/2022

Parsing Objects at a Finer Granularity: A Survey

Fine-grained visual parsing, including fine-grained part segmentation an...

0 Yifan Zhao, et al. ∙

research

∙ 12/28/2022

Part-guided Relational Transformers for Fine-grained Visual Recognition

Fine-grained visual recognition is to classify objects with visually sim...

0 Yifan Zhao, et al. ∙

research

∙ 12/19/2022

Million-scale Object Detection with Large Vision Model

Over the past few years, developing a broad, universal, and general-purp...

0 Feng Lin, et al. ∙

research

∙ 12/06/2022

Event-based Monocular Dense Depth Estimation with Recurrent Transformers

Event cameras, offering high temporal resolutions and high dynamic range...

0 Xu Liu, et al. ∙

research

∙ 11/26/2022

Meta Architecure for Point Cloud Analysis

Recent advances in 3D point cloud analysis bring a diverse set of networ...

0 Haojia Lin, et al. ∙

research

∙ 11/20/2022

Revisiting Color-Event based Tracking: A Unified Network, Dataset, and Metric

Combining the Color and Event cameras (also called Dynamic Vision Sensor...

0 Chuanming Tang, et al. ∙

research

∙ 11/17/2022

HARDVS: Revisiting Human Activity Recognition with Dynamic Vision Sensors

The main streams of human activity recognition (HAR) algorithms are deve...

0 Xiao Wang, et al. ∙

research

∙ 11/02/2022

Unsupervised Deraining: Where Asymmetric Contrastive Learning Meets Self-similarity

Most of the existing learning-based deraining methods are supervisedly t...

0 Yi Chang, et al. ∙

research

∙ 09/29/2022

Spikformer: When Spiking Neural Network Meets Transformer

We consider two biologically plausible structures, the Spiking Neural Ne...

0 Zhaokun Zhou, et al. ∙

research

∙ 09/28/2022

Attention Spiking Neural Networks

Benefiting from the event-driven and sparse spiking characteristics of t...

0 Man Yao, et al. ∙

research

∙ 03/30/2022

Fine-Grained Object Classification via Self-Supervised Pose Alignment

Semantic patterns of fine-grained objects are determined by subtle appea...

0 Xuhui Yang, et al. ∙

research

∙ 03/23/2022

Training-free Transformer Architecture Search

Recently, Vision Transformer (ViT) has achieved remarkable success in se...

30 Qinqin Zhou, et al. ∙

research

∙ 03/10/2022

Annotation Efficient Person Re-Identification with Diverse Cluster-Based Pair Selection

Person Re-identification (Re-ID) has attracted great attention due to it...

0 Lantian Xue, et al. ∙

research

∙ 03/04/2022

Transformations in Learned Image Compression from a Modulation Perspective

In this paper, a unified transformation method in learned image compress...

0 Youneng Bao, et al. ∙

research

∙ 01/25/2022

PowerGear: Early-Stage Power Estimation in FPGA HLS via Heterogeneous Edge-Centric GNNs

Power estimation is the basis of many hardware optimization strategies. ...

4 Zhe Lin, et al. ∙

research

∙ 01/25/2022

Event-based Video Reconstruction via Potential-assisted Spiking Neural Network

Neuromorphic vision sensor is a new bio-inspired imaging paradigm that r...

0 Lin Zhu, et al. ∙

research

∙ 01/21/2022

Deep Reinforcement Learning with Spiking Q-learning

With the help of special neuromorphic hardware, spiking neural networks ...

0 Ding Chen, et al. ∙

research

∙ 11/17/2021

IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization

Learning to synthesize data has emerged as a promising direction in zero...

0 Yunshan Zhong, et al. ∙

research

∙ 09/16/2021

Heterogeneous Relational Complement for Vehicle Re-identification

The crucial problem in vehicle re-identification is to find the same veh...

0 Jiajian Zhao, et al. ∙

research

∙ 09/12/2021

Prioritized Subnet Sampling for Resource-Adaptive Supernet Training

A resource-adaptive supernet adjusts its subnets for inference to fit th...

0 Bohong Chen, et al. ∙

research

∙ 08/19/2021

An Information Theory-inspired Strategy for Automatic Network Pruning

Despite superior performance on many computer vision tasks, deep convolu...

41 Xiawu Zheng, et al. ∙

research

∙ 08/19/2021

Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain

Recently, the generalization behavior of Convolutional Neural Networks (...

12 Guangyao Chen, et al. ∙

research

∙ 07/14/2021

Training Compact CNNs for Image Classification using Dynamic-coded Filter Fusion

The mainstream approach for filter pruning is usually either to force a ...

0 Mingbao Lin, et al. ∙

research

∙ 05/25/2021

Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networks

Spiking Neural Networks (SNNs), as bio-inspired energy-efficient neural ...

0 Jianhao Ding, et al. ∙

research

∙ 05/11/2021

Pruning of Deep Spiking Neural Networks through Gradient Rewiring

Spiking Neural Networks (SNNs) have been attached great importance due t...

0 Yanqi Chen, et al. ∙

research

∙ 04/24/2021

Carrying out CNN Channel Pruning in a White Box

Channel Pruning has been long adopted for compressing CNNs, which signif...

8 Yuxin Zhang, et al. ∙

research

∙ 04/18/2021

Lottery Jackpots Exist in Pre-trained Models

Network pruning is an effective approach to reduce network complexity wi...

0 Yuxin Zhang, et al. ∙

research

∙ 04/10/2021

Spike Camera and Its Coding Methods

This paper introduces a spike camera with a distinct video capture schem...

0 Siwei Dong, et al. ∙

Yonghong Tian

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