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20142023
most citedPruning Filters for Efficient ConvNets

682 citations · 2.5k across the 94 of their papers we have counts for

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39 papers · 1 filter

cs.CV2023

WiCo: Win-win Cooperation of Bottom-up and Top-down Referring Image Segmentation

Zesen Cheng, Peng Jin, Hao Li +5

The top-down and bottom-up methods are two mainstreams of referring segmentation, while both methods have their own intrinsic weaknesses. Top-down methods are chiefly disturbed by…

cs.CV2023

Text-Video Retrieval with Disentangled Conceptualization and Set-to-Set Alignment

Peng Jin, Hao Li, Zesen Cheng +5

Text-video retrieval is a challenging cross-modal task, which aims to align visual entities with natural language descriptions. Current methods either fail to leverage the local de…

cs.CV2023

EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation

Hansheng Chen, Wei Tian, Pichao Wang +3

Locating 3D objects from a single RGB image via Perspective-n-Point (PnP) is a long-standing problem in computer vision. Driven by end-to-end deep learning, recent studies suggest…

cs.CV2023★ 7 cited

DiffusionRet: Generative Text-Video Retrieval with Diffusion Model

Peng Jin, Hao Li, Zesen Cheng +5

Existing text-video retrieval solutions are, in essence, discriminant models focused on maximizing the conditional likelihood, i.e., p(candidates|query). While straightforward, thi…

cs.CV2023

An Adaptive Plug-and-Play Network for Few-Shot Learning

Hao Li, Li Li, Yunmeng Huang +2

Few-shot learning (FSL) requires a model to classify new samples after learning from only a few samples. While remarkable results are achieved in existing methods, the performance…

cs.CV2022★ 1 cited

SteerNeRF: Accelerating NeRF Rendering via Smooth Viewpoint Trajectory

Sicheng Li, Hao Li, Yue Wang +2

Neural Radiance Fields (NeRF) have demonstrated superior novel view synthesis performance but are slow at rendering. To speed up the volume rendering process, many acceleration met…

cs.CV2022★ 4 cited

Unsupervised Visual Defect Detection with Score-Based Generative Model

Yapeng Teng, Haoyang Li, Fuzhen Cai +2

Anomaly Detection (AD), as a critical problem, has been widely discussed. In this paper, we specialize in one specific problem, Visual Defect Detection (VDD), in many industrial ap…

cs.CV2022

Use Classifier as Generator

Haoyang Li

Image recognition/classification is a widely studied problem, but its reverse problem, image generation, has drawn much less attention until recently. But the vast majority of curr…

cs.CV2022★ 28 cited

Toward 3D Spatial Reasoning for Human-like Text-based Visual Question Answering

Hao Li, Jinfa Huang, Peng Jin +3

Text-based Visual Question Answering~(TextVQA) aims to produce correct answers for given questions about the images with multiple scene texts. In most cases, the texts naturally at…

cs.CV2022★ 1 cited

Joint learning of object graph and relation graph for visual question answering

Hao Li, Xu Li, Belhal Karimi +2

Modeling visual question answering(VQA) through scene graphs can significantly improve the reasoning accuracy and interpretability. However, existing models answer poorly for compl…

cs.CV2022

Image-to-Video Re-Identification via Mutual Discriminative Knowledge Transfer

Pichao Wang, Fan Wang, Hao Li

The gap in representations between image and video makes Image-to-Video Re-identification (I2V Re-ID) challenging, and recent works formulate this problem as a knowledge distillati…

cs.CV2021

ELSA: Enhanced Local Self-Attention for Vision Transformer

Jingkai Zhou, Pichao Wang, Fan Wang +3

Self-attention is powerful in modeling long-range dependencies, but it is weak in local finer-level feature learning. The performance of local self-attention (LSA) is just on par w…

cs.CV2021★ 3 cited

Decoupling and Recoupling Spatiotemporal Representation for RGB-D-based Motion Recognition

Benjia Zhou, Pichao Wang, Jun Wan +6

Decoupling spatiotemporal representation refers to decomposing the spatial and temporal features into dimension-independent factors. Although previous RGB-D-based motion recognitio…

cs.CV2021

TransZero: Attribute-guided Transformer for Zero-Shot Learning

Shiming Chen, Ziming Hong, Yang Liu +6

Zero-shot learning (ZSL) aims to recognize novel classes by transferring semantic knowledge from seen classes to unseen ones. Semantic knowledge is learned from attribute descripti…

cs.CV2021★ 5 cited

TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation

Zhaoyuan Yin, Pichao Wang, Fan Wang +4

Unsupervised semantic segmentation aims to obtain high-level semantic representation on low-level visual features without manual annotations. Most existing methods are bottom-up ap…

cs.CV2021★ 47 cited

Self-Supervised Pre-Training for Transformer-Based Person Re-Identification

Hao Luo, Pichao Wang, Yi Xu +5

Transformer-based supervised pre-training achieves great performance in person re-identification (ReID). However, due to the domain gap between ImageNet and ReID datasets, it usual…

cs.CV2021★ 1 cited

2nd Place Solution to Google Landmark Retrieval 2021

Zhang Yuqi, Xu Xianzhe, Chen Weihua +4

This paper presents the 2nd place solution to the Google Landmark Retrieval 2021 Competition on Kaggle. The solution is based on a baseline with training tricks from person re-iden…

cs.CV2021★ 84 cited

HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learning

Shiming Chen, Guo-Sen Xie, Yang Liu +5

Zero-shot learning (ZSL) tackles the unseen class recognition problem, transferring semantic knowledge from seen classes to unseen ones. Typically, to guarantee desirable knowledge…

cs.CV2021

Scaled ReLU Matters for Training Vision Transformers

Pichao Wang, Xue Wang, Hao Luo +5

Vision transformers (ViTs) have been an alternative design paradigm to convolutional neural networks (CNNs). However, the training of ViTs is much harder than CNNs, as it is sensit…

cs.CV2021★ 4 cited

KVT: k-NN Attention for Boosting Vision Transformers

Pichao Wang, Xue Wang, Fan Wang +4

Convolutional Neural Networks (CNNs) have dominated computer vision for years, due to its ability in capturing locality and translation invariance. Recently, many vision transforme…

cs.CV2021★ 2 cited

City-Scale Multi-Camera Vehicle Tracking Guided by Crossroad Zones

Chong Liu, Yuqi Zhang, Hao Luo +6

Multi-Target Multi-Camera Tracking has a wide range of applications and is the basis for many advanced inferences and predictions. This paper describes our solution to the Track 3…

cs.CV2021★ 1 cited

Unsupervised Visual Representation Learning by Online Constrained K-Means

Qi Qian, Yuanhong Xu, Juhua Hu +2

Cluster discrimination is an effective pretext task for unsupervised representation learning, which often consists of two phases: clustering and discrimination. Clustering is to as…

cs.CV2021★ 3 cited

An Efficient Training Approach for Very Large Scale Face Recognition

Kai Wang, Shuo Wang, Panpan Zhang +7

Face recognition has achieved significant progress in deep learning era due to the ultra-large-scale and welllabeled datasets. However, training on the outsize datasets is time-con…

cs.CV2021★ 13 cited

PlenOctrees for Real-time Rendering of Neural Radiance Fields

Alex Yu, Ruilong Li, Matthew Tancik +3

We introduce a method to render Neural Radiance Fields (NeRFs) in real time using PlenOctrees, an octree-based 3D representation which supports view-dependent effects. Our method c…