Baochang Zhang

research

∙ 09/18/2023

Heterogeneous Generative Knowledge Distillation with Masked Image Modeling

Small CNN-based models usually require transferring knowledge from a lar...

0 Ziming Wang, et al. ∙

research

∙ 08/20/2023

Representation Disparity-aware Distillation for 3D Object Detection

In this paper, we focus on developing knowledge distillation (KD) for co...

0 Yanjing Li, et al. ∙

research

∙ 07/01/2023

Filter Pruning for Efficient CNNs via Knowledge-driven Differential Filter Sampler

Filter pruning simultaneously accelerates the computation and reduces th...

0 Shaohui Lin, et al. ∙

research

∙ 06/27/2023

DCP-NAS: Discrepant Child-Parent Neural Architecture Search for 1-bit CNNs

Neural architecture search (NAS) proves to be among the effective approa...

0 Yanjing Li, et al. ∙

research

∙ 05/21/2023

Bi-ViT: Pushing the Limit of Vision Transformer Quantization

Vision transformers (ViTs) quantization offers a promising prospect to f...

0 Yanjing Li, et al. ∙

research

∙ 05/19/2023

AttriCLIP: A Non-Incremental Learner for Incremental Knowledge Learning

Continual learning aims to enable a model to incrementally learn knowled...

0 Runqi Wang, et al. ∙

research

∙ 05/19/2023

Few-Shot Learning with Visual Distribution Calibration and Cross-Modal Distribution Alignment

Pre-trained vision-language models have inspired much research on few-sh...

0 Runqi Wang, et al. ∙

research

∙ 05/17/2023

Controllable Mind Visual Diffusion Model

Brain signal visualization has emerged as an active research area, servi...

0 Bohan Zeng, et al. ∙

research

∙ 04/14/2023

MVP-SEG: Multi-View Prompt Learning for Open-Vocabulary Semantic Segmentation

CLIP (Contrastive Language-Image Pretraining) is well-developed for open...

0 Jie Guo, et al. ∙

research

∙ 04/06/2023

Face Animation with an Attribute-Guided Diffusion Model

Face animation has achieved much progress in computer vision. However, p...

0 Bohan Zeng, et al. ∙

research

∙ 04/01/2023

Q-DETR: An Efficient Low-Bit Quantized Detection Transformer

The recent detection transformer (DETR) has advanced object detection, b...

0 Sheng Xu, et al. ∙

research

∙ 03/29/2023

Implicit Diffusion Models for Continuous Super-Resolution

Image super-resolution (SR) has attracted increasing attention due to it...

0 Sicheng Gao, et al. ∙

research

∙ 03/03/2023

Confidence-driven Bounding Box Localization for Small Object Detection

Despite advancements in generic object detection, there remains a perfor...

0 Huixin Sun, et al. ∙

research

∙ 02/02/2023

Resilient Binary Neural Network

Binary neural networks (BNNs) have received ever-increasing popularity f...

0 Sheng Xu, et al. ∙

research

∙ 12/12/2022

Feature Calibration Network for Occluded Pedestrian Detection

Pedestrian detection in the wild remains a challenging problem especiall...

0 Tianliang Zhang, et al. ∙

research

∙ 12/12/2022

CircleNet: Reciprocating Feature Adaptation for Robust Pedestrian Detection

Pedestrian detection in the wild remains a challenging problem especiall...

0 Tianliang Zhang, et al. ∙

research

∙ 11/28/2022

Rethinking the Number of Shots in Robust Model-Agnostic Meta-Learning

Robust Model-Agnostic Meta-Learning (MAML) is usually adopted to train a...

0 Xiaoyue Duan, et al. ∙

research

∙ 10/13/2022

Q-ViT: Accurate and Fully Quantized Low-bit Vision Transformer

The large pre-trained vision transformers (ViTs) have demonstrated remar...

0 Yanjing Li, et al. ∙

research

∙ 10/07/2022

IDa-Det: An Information Discrepancy-aware Distillation for 1-bit Detectors

Knowledge distillation (KD) has been proven to be useful for training co...

0 Sheng Xu, et al. ∙

research

∙ 09/21/2022

FNeVR: Neural Volume Rendering for Face Animation

Face animation, one of the hottest topics in computer vision, has achiev...

0 Bohan Zeng, et al. ∙

research

∙ 09/04/2022

Recurrent Bilinear Optimization for Binary Neural Networks

Binary Neural Networks (BNNs) show great promise for real-world embedded...

0 Sheng Xu, et al. ∙

research

∙ 08/31/2022

MAFormer: A Transformer Network with Multi-scale Attention Fusion for Visual Recognition

Vision Transformer and its variants have demonstrated great potential in...

0 Yunhao Wang, et al. ∙

research

∙ 08/27/2022

Anti-Retroactive Interference for Lifelong Learning

Humans can continuously learn new knowledge. However, machine learning m...

1 Runqi Wang, et al. ∙

research

∙ 03/24/2022

Bi-level Doubly Variational Learning for Energy-based Latent Variable Models

Energy-based latent variable models (EBLVMs) are more expressive than co...

0 Ge Kan, et al. ∙

research

∙ 03/17/2022

Confidence Dimension for Deep Learning based on Hoeffding Inequality and Relative Evaluation

Research on the generalization ability of deep neural networks (DNNs) ha...

10 Runqi Wang, et al. ∙

research

∙ 01/20/2022

TerViT: An Efficient Ternary Vision Transformer

Vision transformers (ViTs) have demonstrated great potential in various ...

0 Sheng Xu, et al. ∙

research

∙ 12/28/2021

Associative Adversarial Learning Based on Selective Attack

A human's attention can intuitively adapt to corrupted areas of an image...

10 Runqi Wang, et al. ∙

research

∙ 12/15/2021

Self-Supervised Monocular Depth and Ego-Motion Estimation in Endoscopy: Appearance Flow to the Rescue

Recently, self-supervised learning technology has been applied to calcul...

2 Shuwei Shao, et al. ∙

research

∙ 11/26/2021

POEM: 1-bit Point-wise Operations based on Expectation-Maximization for Efficient Point Cloud Processing

Real-time point cloud processing is fundamental for lots of computer vis...

0 Sheng Xu, et al. ∙

research

∙ 11/17/2021

IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization

Learning to synthesize data has emerged as a promising direction in zero...

0 Yunshan Zhong, et al. ∙

research

∙ 11/16/2021

NENet: Monocular Depth Estimation via Neural Ensembles

Depth estimation is getting a widespread popularity in the computer visi...

15 Shuwei Shao, et al. ∙

research

∙ 09/12/2021

Prioritized Subnet Sampling for Resource-Adaptive Supernet Training

A resource-adaptive supernet adjusts its subnets for inference to fit th...

0 Bohong Chen, et al. ∙

research

∙ 06/20/2021

Cogradient Descent for Dependable Learning

Conventional gradient descent methods compute the gradients for multiple...

0 Runqi Wang, et al. ∙

research

∙ 06/06/2021

Oriented Object Detection with Transformer

Object detection with Transformers (DETR) has achieved a competitive per...

0 Teli Ma, et al. ∙

research

∙ 05/07/2021

Probabilistic Ranking-Aware Ensembles for Enhanced Object Detections

Model ensembles are becoming one of the most effective approaches for im...

0 Mingyuan Mao, et al. ∙

research

∙ 03/08/2021

Interpretable Attention Guided Network for Fine-grained Visual Classification

Fine-grained visual classification (FGVC) is challenging but more critic...

5 Zhenhuan Huang, et al. ∙

research

∙ 02/16/2021

SiMaN: Sign-to-Magnitude Network Binarization

Binary neural networks (BNNs) have attracted broad research interest due...

0 Mingbao Lin, et al. ∙

research

∙ 02/03/2021

Multi-UAV Mobile Edge Computing and Path Planning Platform based on Reinforcement Learning

Unmanned Aerial vehicles (UAVs) are widely used as network processors in...

0 Huan Chang, et al. ∙

research

∙ 12/07/2020

Deformable Gabor Feature Networks for Biomedical Image Classification

In recent years, deep learning has dominated progress in the field of me...

33 Xuan Gong, et al. ∙

research

∙ 12/01/2020

Fast Class-wise Updating for Online Hashing

Online image hashing has received increasing research attention recently...

0 Mingbao Lin, et al. ∙

research

∙ 11/24/2020

A Review of Recent Advances of Binary Neural Networks for Edge Computing

Edge computing is promising to become one of the next hottest topics in ...

0 Wenyu Zhao, et al. ∙

research

∙ 11/09/2020

PAMS: Quantized Super-Resolution via Parameterized Max Scale

Deep convolutional neural networks (DCNNs) have shown dominant performan...

0 Huixia Li, et al. ∙

research

∙ 09/28/2020

Rotated Binary Neural Network

Binary Neural Network (BNN) shows its predominance in reducing the compl...

0 Mingbao Lin, et al. ∙

research

∙ 09/16/2020

The 1st Tiny Object Detection Challenge:Methods and Results

The 1st Tiny Object Detection (TOD) Challenge aims toencourage research ...

16 Xuehui Yu, et al. ∙

research

∙ 09/08/2020

Binarized Neural Architecture Search for Efficient Object Recognition

Traditional neural architecture search (NAS) has a significant impact in...

0 Hanlin Chen, et al. ∙

research

∙ 08/03/2020

Anti-Bandit Neural Architecture Search for Model Defense

Deep convolutional neural networks (DCNNs) have dominated as the best pe...

10 Hanlin Chen, et al. ∙

research

∙ 06/23/2020

iffDetector: Inference-aware Feature Filtering for Object Detection

Modern CNN-based object detectors focus on feature configuration during ...

0 Mingyuan Mao, et al. ∙

research

∙ 06/16/2020

Cogradient Descent for Bilinear Optimization

Conventional learning methods simplify the bilinear model by regarding t...

0 Li'an Zhuo, et al. ∙

research

∙ 02/29/2020

NAS-Count: Counting-by-Density with Neural Architecture Search

Most of the recent advances in crowd counting have evolved from hand-des...

0 Yutao Hu, et al. ∙

research

∙ 02/24/2020

HRank: Filter Pruning using High-Rank Feature Map

Neural network pruning offers a promising prospect to facilitate deployi...

7 Mingbao Lin, et al. ∙

Baochang Zhang

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