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08/18/2023
Point Contrastive Prediction with Semantic Clustering for Self-Supervised Learning on Point Cloud Videos
We propose a unified point cloud video self-supervised learning framewor...
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08/18/2023
Masked Spatio-Temporal Structure Prediction for Self-supervised Learning on Point Cloud Videos
Recently, the community has made tremendous progress in developing effec...
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07/01/2023
Variation-aware Vision Transformer Quantization
Despite the remarkable performance of Vision Transformers (ViTs) in vari...
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06/22/2023
Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective
We present a new dataset condensation framework termed Squeeze, Recover ...
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06/13/2023
One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning
We present Generalized LoRA (GLoRA), an advanced approach for universal ...
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05/22/2023
Contrastive Predictive Autoencoders for Dynamic Point Cloud Self-Supervised Learning
We present a new self-supervised paradigm on point cloud sequence unders...
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05/06/2023
PointCMP: Contrastive Mask Prediction for Self-supervised Learning on Point Cloud Videos
Self-supervised learning can extract representations of good quality fro...
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03/02/2023
Dropout Reduces Underfitting
Introduced by Hinton et al. in 2012, dropout has stood the test of time ...
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01/11/2023
Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation
High-quality pseudo labels are essential for semi-supervised semantic se...
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12/11/2022
PromptCAL: Contrastive Affinity Learning via Auxiliary Prompts for Generalized Novel Category Discovery
Although existing semi-supervised learning models achieve remarkable suc...
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10/20/2022
i-MAE: Are Latent Representations in Masked Autoencoders Linearly Separable?
Masked image modeling (MIM) has been recognized as a strong and popular ...
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10/20/2022
MixMask: Revisiting Masked Siamese Self-supervised Learning in Asymmetric Distance
Recent advances in self-supervised learning integrate Masked Modeling an...
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01/03/2022
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space
This paper explores the feasibility of finding an optimal sub-model from...
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12/03/2021
Data-Free Neural Architecture Search via Recursive Label Calibration
This paper aims to explore the feasibility of neural architecture search...
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12/02/2021
A Fast Knowledge Distillation Framework for Visual Recognition
While Knowledge Distillation (KD) has been recognized as a useful tool i...
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11/29/2021
Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation
The nonuniform quantization strategy for compressing neural networks usu...
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11/09/2021
Sliced Recursive Transformer
We present a neat yet effective recursive operation on vision transforme...
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10/11/2021
Multi-modal Self-supervised Pre-training for Regulatory Genome Across Cell Types
In the genome biology research, regulatory genome modeling is an importa...
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06/21/2021
How Do Adam and Training Strategies Help BNNs Optimization?
The best performing Binary Neural Networks (BNNs) are usually attained u...
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05/23/2021
COTR: Convolution in Transformer Network for End to End Polyp Detection
Purpose: Colorectal cancer (CRC) is the second most common cause of canc...
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04/16/2021
"BNN - BN = ?": Training Binary Neural Networks without Batch Normalization
Batch normalization (BN) is a key facilitator and considered essential f...
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04/01/2021
Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study
This work aims to empirically clarify a recently discovered perspective ...
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03/30/2021
Unsupervised Disentanglement of Linear-Encoded Facial Semantics
We propose a method to disentangle linear-encoded facial semantics from ...
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02/22/2021
Interpretative Computer-aided Lung Cancer Diagnosis: from Radiology Analysis to Malignancy Evaluation
Background and Objective:Computer-aided diagnosis (CAD) systems promote ...
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02/17/2021
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration
Previous studies dominantly target at self-supervised learning on real-v...
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02/08/2021
Partial Is Better Than All: Revisiting Fine-tuning Strategy for Few-shot Learning
The goal of few-shot learning is to learn a classifier that can recogniz...
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11/29/2020
Conditional Link Prediction of Category-Implicit Keypoint Detection
Keypoints of objects reflect their concise abstractions, while the corre...
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11/15/2020
Online Ensemble Model Compression using Knowledge Distillation
This paper presents a novel knowledge distillation based model compressi...
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09/17/2020
MEAL V2: Boosting Vanilla ResNet-50 to 80 without Tricks
In this paper, we introduce a simple yet effective approach that can boo...
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09/07/2020
Channel-wise Alignment for Adaptive Object Detection
Generic object detection has been immensely promoted by the development ...
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06/26/2020
Cross-Ssupervised Object Detection
After learning a new object category from image-level annotations (with ...
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06/26/2020
Cross-Supervised Object Detection
After learning a new object category from image-level annotations (with ...
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05/18/2020
Joint Multi-Dimension Pruning
We present joint multi-dimension pruning (named as JointPruning), a new ...
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05/13/2020
Binarizing MobileNet via Evolution-based Searching
Binary Neural Networks (BNNs), known to be one among the effectively com...
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03/29/2020
Attentive CutMix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification
Convolutional neural networks (CNN) are capable of learning robust repre...
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03/11/2020
Rethinking Image Mixture for Unsupervised Visual Representation Learning
In supervised learning, smoothing label/prediction distribution in neura...
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03/07/2020
ReActNet: Towards Precise Binary Neural Network with Generalized Activation Functions
In this paper, we propose several ideas for enhancing a binary network t...
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02/12/2020
Solving Missing-Annotation Object Detection with Background Recalibration Loss
This paper focuses on a novel and challenging detection scenario: A majo...
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11/27/2019
Soft Anchor-Point Object Detection
Recently, anchor-free detectors have shown great potential to outperform...
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11/06/2019
SCL: Towards Accurate Domain Adaptive Object Detection via Gradient Detach Based Stacked Complementary Losses
Unsupervised domain adaptive object detection aims to learn a robust det...
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10/21/2019
Transferable Recognition-Aware Image Processing
Recent progress in image recognition has stimulated the deployment of vi...
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08/22/2019
Adversarial-Based Knowledge Distillation for Multi-Model Ensemble and Noisy Data Refinement
Generic Image recognition is a fundamental and fairly important visual p...
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07/29/2019
MoBiNet: A Mobile Binary Network for Image Classification
MobileNet and Binary Neural Networks are two among the most widely used ...
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05/05/2019
Towards Instance-level Image-to-Image Translation
Unpaired Image-to-image Translation is a new rising and challenging visi...
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02/25/2019
Transfer Learning for Sequences via Learning to Collocate
Transfer learning aims to solve the data sparsity for a target domain by...
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12/06/2018
MEAL: Multi-Model Ensemble via Adversarial Learning
Often the best performing deep neural models are ensembles of multiple b...
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09/25/2018
Object Detection from Scratch with Deep Supervision
We propose Deeply Supervised Object Detectors (DSOD), an object detectio...
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07/13/2018
TS2C: Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection
This work provides a simple approach to discover tight object bounding b...
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12/04/2017
Learning Object Detectors from Scratch with Gated Recurrent Feature Pyramids
In this paper, we propose gated recurrent feature pyramid for the proble...
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08/22/2017
