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07/12/2023
Unsupervised Optical Flow Estimation with Dynamic Timing Representation for Spike Camera
Efficiently selecting an appropriate spike stream data length to extract...
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07/11/2023
Generative Pretraining in Multimodality
We present Emu, a Transformer-based multimodal foundation model, which c...
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07/03/2023
Unveiling the Potential of Spike Streams for Foreground Occlusion Removal from Densely Continuous Views
The extraction of a clean background image by removing foreground occlus...
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06/21/2023
Mitigating Communication Costs in Neural Networks: The Role of Dendritic Nonlinearity
Our comprehension of biological neuronal networks has profoundly influen...
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06/09/2023
Spike timing reshapes robustness against attacks in spiking neural networks
The success of deep learning in the past decade is partially shrouded in...
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05/26/2023
HUB: Guiding Learned Optimizers with Continuous Prompt Tuning
Learned optimizers are a crucial component of meta-learning. Recent adva...
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04/06/2023
SegGPT: Segmenting Everything In Context
We present SegGPT, a generalist model for segmenting everything in conte...
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04/06/2023
Spike Stream Denoising via Spike Camera Simulation
As a neuromorphic sensor with high temporal resolution, the spike camera...
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03/29/2023
Exploring Asymmetric Tunable Blind-Spots for Self-supervised Denoising in Real-World Scenarios
Self-supervised denoising has attracted widespread attention due to its ...
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03/21/2023
SpikeCV: Open a Continuous Computer Vision Era
SpikeCV is a new open-source computer vision platform for the spike came...
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03/20/2023
EVA-02: A Visual Representation for Neon Genesis
We launch EVA-02, a next-generation Transformer-based visual representat...
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03/19/2023
CLIP4MC: An RL-Friendly Vision-Language Model for Minecraft
One of the essential missions in the AI research community is to build a...
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03/08/2023
Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks
Spiking Neural Networks (SNNs) have gained great attraction due to their...
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02/21/2023
Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes
Spiking Neural Networks (SNNs) have attracted great attention due to the...
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02/14/2023
Hard-aware Instance Adaptive Self-training for Unsupervised Cross-domain Semantic Segmentation
The divergence between labeled training data and unlabeled testing data ...
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02/04/2023
Reducing ANN-SNN Conversion Error through Residual Membrane Potential
Spiking Neural Networks (SNNs) have received extensive academic attentio...
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12/05/2022
Images Speak in Images: A Generalist Painter for In-Context Visual Learning
In-context learning, as a new paradigm in NLP, allows the model to rapid...
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11/14/2022
EVA: Exploring the Limits of Masked Visual Representation Learning at Scale
We launch EVA, a vision-centric foundation model to explore the limits o...
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10/25/2022
Entity Divider with Language Grounding in Multi-Agent Reinforcement Learning
We investigate the use of natural language to drive the generalization o...
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09/26/2022
Multi-Agent Sequential Decision-Making via Communication
Communication helps agents to obtain information about others so that be...
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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...
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02/03/2022
Optimized Potential Initialization for Low-latency Spiking Neural Networks
Spiking Neural Networks (SNNs) have been attached great importance due t...
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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...
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01/21/2022
Deep Reinforcement Learning with Spiking Q-learning
With the help of special neuromorphic hardware, spiking neural networks ...
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01/04/2022
A Robust Visual Sampling Model Inspired by Receptive Field
Spike camera mimicking the retina fovea can report per-pixel luminance i...
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11/29/2021
Point-BERT: Pre-training 3D Point Cloud Transformers with Masked Point Modeling
We present Point-BERT, a new paradigm for learning Transformers to gener...
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10/08/2021
SCFlow: Optical Flow Estimation for Spiking Camera
As a bio-inspired sensor with high temporal resolution, Spiking camera h...
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09/10/2021
Spatio-Temporal Recurrent Networks for Event-Based Optical Flow Estimation
Event camera has offered promising alternative for visual perception, es...
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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 ...
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05/11/2021
Pruning of Deep Spiking Neural Networks through Gradient Rewiring
Spiking Neural Networks (SNNs) have been attached great importance due t...
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04/10/2021
Spike Camera and Its Coding Methods
This paper introduces a spike camera with a distinct video capture schem...
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02/08/2021
Spike-based Residual Blocks
Deep Spiking Neural Networks (SNNs) are harder to train than ANNs becaus...
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10/31/2020
Learning Open Set Network with Discriminative Reciprocal Points
Open set recognition is an emerging research area that aims to simultane...
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10/16/2020
Human Perception-based Evaluation Criterion for Ultra-high Resolution Cell Membrane Segmentation
Computer vision technology is widely used in biological and medical data...
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06/11/2020
Learning Individually Inferred Communication for Multi-Agent Cooperation
Communication lays the foundation for human cooperation. It is also cruc...
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03/11/2020
Kernel Quantization for Efficient Network Compression
This paper presents a novel network compression framework Kernel Quantiz...
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01/10/2020
Video Coding for Machines: A Paradigm of Collaborative Compression and Intelligent Analytics
Video coding, which targets to compress and reconstruct the whole frame,...
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12/20/2019
Unsupervised Few-shot Learning via Self-supervised Training
Learning from limited exemplars (few-shot learning) is a fundamental, un...
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12/20/2019
An Efficient Coding Method for Spike Camera using Inter-Spike Intervals
Recently, a novel bio-inspired spike camera has been proposed, which con...
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10/05/2019
Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning
Few-shot learning, which aims at extracting new concepts rapidly from ex...
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07/28/2019
Spatiotemporal Information Processing with a Reservoir Decision-making Network
Spatiotemporal information processing is fundamental to brain functions....
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07/20/2019
A Retina-inspired Sampling Method for Visual Texture Reconstruction
Conventional frame-based camera is not able to meet the demand of rapid ...
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05/06/2019
P-ODN: Prototype based Open Deep Network for Open Set Recognition
Most of the existing recognition algorithms are proposed for closed set ...
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04/30/2019
Reconstruction of Natural Visual Scenes from Neural Spikes with Deep Neural Networks
Neural coding is one of the central questions in systems neuroscience fo...
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02/28/2019
Bi-Directional Cascade Network for Perceptual Edge Detection
Exploiting multi-scale representations is critical to improve edge detec...
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02/22/2019
Probabilistic Inference of Binary Markov Random Fields in Spiking Neural Networks through Mean-field Approximation
Recent studies have suggested that the cognitive process of the human br...
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11/19/2018
Multi-scale 3D Convolution Network for Video Based Person Re-Identification
This paper proposes a two-stream convolution network to extract spatial ...
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11/06/2018
Revealing Fine Structures of the Retinal Receptive Field by Deep Learning Networks
Deep convolutional neural networks (CNNs) have demonstrated impressive p...
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08/12/2018
Neural System Identification with Spike-triggered Non-negative Matrix Factorization
Neuronal circuits formed in the brain are complex with intricate connect...
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08/12/2018