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20162026
most citedAdversarial Reciprocal Points Learning for Open Set Recognition

345 citations · 2.2k across the 88 of their papers we have counts for

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64 papers · 1 filter

cs.CV2026

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…

cs.CV2023★ 52 cited

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…

cs.CV2023★ 59 cited

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…

cs.CV2023★ 4 cited

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…

cs.CV2023★ 14 cited

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…

cs.CV2022★ 5 cited

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…

cs.CV2022★ 82 cited

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…

cs.CV2022★ 5 cited

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…

cs.CV2022

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…

cs.CV2022★ 8 cited

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…

cs.CV2022★ 14 cited

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…

cs.CV2022

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…

cs.CV2022★ 7 cited

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…

cs.CV2022

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…

cs.CV2022★ 97 cited

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…

cs.CV2022★ 6 cited

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…

cs.CV2021★ 4 cited

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…

cs.CV2021

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…

cs.CV2021

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…

cs.CV2021★ 1 cited

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…

cs.CV2021★ 11 cited

An Information Theory-inspired Strategy for Automatic Network Pruning

Xiawu Zheng, Yuexiao Ma, Teng Xi +6

Despite superior performance on many computer vision tasks, deep convolution neural networks are well known to be compressed on devices that have resource constraints. Most existin…

cs.CV2021★ 20 cited

VisEvent: Reliable Object Tracking via Collaboration of Frame and Event Flows

Xiao Wang, Jianing Li, Lin Zhu +6

Different from visible cameras which record intensity images frame by frame, the biologically inspired event camera produces a stream of asynchronous and sparse events with much lo…

cs.CV2021★ 2 cited

MFGNet: Dynamic Modality-Aware Filter Generation for RGB-T Tracking

Xiao Wang, Xiujun Shu, Shiliang Zhang +4

Many RGB-T trackers attempt to attain robust feature representation by utilizing an adaptive weighting scheme (or attention mechanism). Different from these works, we propose a new…

cs.CV2021★ 6 cited

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

Mingbao Lin, Bohong Chen, Fei Chao +1

The mainstream approach for filter pruning is usually either to force a hard-coded importance estimation upon a computation-heavy pretrained model to select "important" filters, or…