345 citations · 2.2k across the 88 of their papers we have counts for
88 papers
QCA: Query- and Content-Aware Keyframe Selection for Long Video Understanding
Jun Peng, Baiyang Song, Jie Li +4
Video understanding is often plagued by severe temporal redundancy, where processing dense frame sequences is both semantically inefficient and computationally expensive. This chal…
Retina gap junctions support the robust perception by warping neural representational geometries along the visual hierarchy
Yang Yue, Shenjian Zhang, Yonghong Tian +2
Deep Neural Networks (DNNs) are vulnerable to elaborately designed adversarial noise, although they have achieved extraordinary success in many tasks. Compared with DNNs, the human…
Fully Spiking Actor Network with Intra-layer Connections for Reinforcement 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…
SODFormer: Streaming Object Detection with Transformer Using Events and Frames
Dianze Li, Jianing Li, Yonghong Tian
DAVIS camera, streaming two complementary sensing modalities of asynchronous events and frames, has gradually been used to address major object detection challenges (e.g., fast mot…
Dual Adaptive Representation Alignment for Cross-domain Few-shot Learning
Yifan Zhao, Tong Zhang, Jia Li +1
Few-shot learning aims to recognize novel queries with limited support samples by learning from base knowledge. Recent progress in this setting assumes that the base knowledge and…
Picking Up Quantization Steps for Compressed Image Classification
Li Ma, Peixi Peng, Guangyao Chen +3
The sensitivity of deep neural networks to compressed images hinders their usage in many real applications, which means classification networks may fail just after taking a screens…
Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey
Xiao Wang, Guangyao Chen, Guangwu Qian +5
With the urgent demand for generalized deep models, many pre-trained big models are proposed, such as BERT, ViT, GPT, etc. Inspired by the success of these models in single domains…
Parsing Objects at a Finer Granularity: A Survey
Yifan Zhao, Jia Li, Yonghong Tian
Fine-grained visual parsing, including fine-grained part segmentation and fine-grained object recognition, has attracted considerable critical attention due to its importance in ma…
Part-guided Relational Transformers for Fine-grained Visual Recognition
Yifan Zhao, Jia Li, Xiaowu Chen +1
Fine-grained visual recognition is to classify objects with visually similar appearances into subcategories, which has made great progress with the development of deep CNNs. Howeve…
Event-based Monocular Dense Depth Estimation with Recurrent Transformers
Xu Liu, Jianing Li, Xiaopeng Fan +1
Event cameras, offering high temporal resolutions and high dynamic ranges, have brought a new perspective to address common challenges (e.g., motion blur and low light) in monocula…
Universal Object Detection with Large Vision Model
Feng Lin, Wenze Hu, Yaowei Wang +5
Over the past few years, there has been growing interest in developing a broad, universal, and general-purpose computer vision system. Such systems have the potential to address a…
HARDVS: Revisiting Human Activity Recognition with Dynamic Vision Sensors
Xiao Wang, Zongzhen Wu, Bo Jiang +5
The main streams of human activity recognition (HAR) algorithms are developed based on RGB cameras which are suffered from illumination, fast motion, privacy-preserving, and large…
Revisiting Color-Event based Tracking: A Unified Network, Dataset, and Metric
Chuanming Tang, Xiao Wang, Ju Huang +5
Combining the Color and Event cameras (also called Dynamic Vision Sensors, DVS) for robust object tracking is a newly emerging research topic in recent years. Existing color-event…
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…
Fine-Grained Object Classification via Self-Supervised Pose Alignment
Xuhui Yang, Yaowei Wang, Ke Chen +2
Semantic patterns of fine-grained objects are determined by subtle appearance difference of local parts, which thus inspires a number of part-based methods. However, due to uncontr…
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…
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…
PowerGear: Early-Stage Power Estimation in FPGA HLS via Heterogeneous Edge-Centric GNNs
Zhe Lin, Zike Yuan, Jieru Zhao +3
Power estimation is the basis of many hardware optimization strategies. However, it is still challenging to offer accurate power estimation at an early stage such as high-level syn…
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…
IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization
Yunshan Zhong, Mingbao Lin, Gongrui Nan +4
Learning to synthesize data has emerged as a promising direction in zero-shot quantization (ZSQ), which represents neural networks by low-bit integer without accessing any of the r…
Heterogeneous Relational Complement for Vehicle Re-identification
Jiajian Zhao, Yifan Zhao, Jia Li +2
The crucial problem in vehicle re-identification is to find the same vehicle identity when reviewing this object from cross-view cameras, which sets a higher demand for learning vi…
Prioritized Subnet Sampling for Resource-Adaptive Supernet Training
Bohong Chen, Mingbao Lin, Rongrong Ji +1
A resource-adaptive supernet adjusts its subnets for inference to fit the dynamically available resources. In this paper, we propose prioritized subnet sampling to train a resource…
Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain
Guangyao Chen, Peixi Peng, Li Ma +3
Recently, the generalization behavior of Convolutional Neural Networks (CNN) is gradually transparent through explanation techniques with the frequency components decomposition. Ho…