262 citations · 1.9k across the 56 of their papers we have counts for
8 papers · 1 filter
EVA: Exploring the Limits of Masked Visual Representation Learning at Scale
Yuxin Fang, Wen Wang, Binhui Xie +6
We launch EVA, a vision-centric foundation model to explore the limits of visual representation at scale using only publicly accessible data. EVA is a vanilla ViT pre-trained to re…
Images Speak in Images: A Generalist Painter for In-Context Visual Learning
Xinlong Wang, Wen Wang, Yue Cao +2
In-context learning, as a new paradigm in NLP, allows the model to rapidly adapt to various tasks with only a handful of prompts and examples. But in computer vision, the difficult…
Temporal Up-Sampling for Asynchronous Events
Xijie Xiang, Lin Zhu, Jianing Li +2
The event camera is a novel bio-inspired vision sensor. When the brightness change exceeds the preset threshold, the sensor generates events asynchronously. The number of valid eve…
Annotation Efficient Person Re-Identification with Diverse Cluster-Based Pair Selection
Lantian Xue, Yixiong Zou, Peixi Peng +2
Person Re-identification (Re-ID) has attracted great attention due to its promising real-world applications. However, in practice, it is always costly to annotate the training data…
1000x Faster Camera and Machine Vision with Ordinary Devices
Tiejun Huang, Yajing Zheng, Zhaofei Yu +13
In digital cameras, we find a major limitation: the image and video form inherited from a film camera obstructs it from capturing the rapidly changing photonic world. Here, we pres…
A Robust Visual Sampling Model Inspired by Receptive Field
Liwen Hu, Lei Ma, Dawei Weng +1
Spike camera mimicking the retina fovea can report per-pixel luminance intensity accumulation by firing spikes. As a bio-inspired vision sensor with high temporal resolution, it ha…
Event-based Video Reconstruction via Potential-assisted Spiking Neural Network
Lin Zhu, Xiao Wang, Yi Chang +3
Neuromorphic vision sensor is a new bio-inspired imaging paradigm that reports asynchronous, continuously per-pixel brightness changes called `events' with high temporal resolution…
Deep Reinforcement Learning with Spiking Q-learning
Ding Chen, Peixi Peng, Tiejun Huang +1
With the help of special neuromorphic hardware, spiking neural networks (SNNs) are expected to realize artificial intelligence (AI) with less energy consumption. It provides a prom…