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08/27/2023
Unified and Dynamic Graph for Temporal Character Grouping in Long Videos
Video temporal character grouping locates appearing moments of major cha...
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08/20/2023
Representation Disparity-aware Distillation for 3D Object Detection
In this paper, we focus on developing knowledge distillation (KD) for co...
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08/16/2023
MemoChat: Tuning LLMs to Use Memos for Consistent Long-Range Open-Domain Conversation
We propose MemoChat, a pipeline for refining instructions that enables l...
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06/09/2023
Spatial Re-parameterization for N:M Sparsity
This paper presents a Spatial Re-parameterization (SpRe) method for the ...
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05/29/2023
DiffRate : Differentiable Compression Rate for Efficient Vision Transformers
Token compression aims to speed up large-scale vision transformers (e.g....
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05/21/2023
Bi-ViT: Pushing the Limit of Vision Transformer Quantization
Vision transformers (ViTs) quantization offers a promising prospect to f...
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05/14/2023
MultiQuant: A Novel Multi-Branch Topology Method for Arbitrary Bit-width Network Quantization
Arbitrary bit-width network quantization has received significant attent...
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05/10/2023
Distribution-Flexible Subset Quantization for Post-Quantizing Super-Resolution Networks
This paper introduces Distribution-Flexible Subset Quantization (DFSQ), ...
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04/01/2023
Q-DETR: An Efficient Low-Bit Quantized Detection Transformer
The recent detection transformer (DETR) has advanced object detection, b...
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02/13/2023
Bi-directional Masks for Efficient N:M Sparse Training
We focus on addressing the dense backward propagation issue for training...
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02/02/2023
Resilient Binary Neural Network
Binary neural networks (BNNs) have received ever-increasing popularity f...
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01/26/2023
Low-Rank Winograd Transformation for 3D Convolutional Neural Networks
This paper focuses on Winograd transformation in 3D convolutional neural...
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12/29/2022
Discriminator-Cooperated Feature Map Distillation for GAN Compression
Despite excellent performance in image generation, Generative Adversaria...
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12/26/2022
SMMix: Self-Motivated Image Mixing for Vision Transformers
CutMix is a vital augmentation strategy that determines the performance ...
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12/21/2022
Exploring Content Relationships for Distilling Efficient GANs
This paper proposes a content relationship distillation (CRD) to tackle ...
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12/08/2022
Shadow Removal by High-Quality Shadow Synthesis
Most shadow removal methods rely on the invasion of training images asso...
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11/12/2022
Exploiting the Partly Scratch-off Lottery Ticket for Quantization-Aware Training
Quantization-aware training (QAT) receives extensive popularity as it we...
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08/27/2022
LAB-Net: LAB Color-Space Oriented Lightweight Network for Shadow Removal
This paper focuses on the limitations of current over-parameterized shad...
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07/12/2022
Knowledge Condensation Distillation
Knowledge Distillation (KD) transfers the knowledge from a high-capacity...
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06/14/2022
Learning Best Combination for Efficient N:M Sparsity
By forcing at most N out of M consecutive weights to be non-zero, the re...
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05/23/2022
Super Vision Transformer
We attempt to reduce the computational costs in vision transformers (ViT...
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05/10/2022
Shadow-Aware Dynamic Convolution for Shadow Removal
With a wide range of shadows in many collected images, shadow removal ha...
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03/30/2022
SeqTR: A Simple yet Universal Network for Visual Grounding
In this paper, we propose a simple yet universal network termed SeqTR fo...
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03/21/2022
ARM: Any-Time Super-Resolution Method
This paper proposes an Any-time super-Resolution Method (ARM) to tackle ...
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03/08/2022
Dynamic Dual Trainable Bounds for Ultra-low Precision Super-Resolution Networks
Light-weight super-resolution (SR) models have received considerable att...
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03/08/2022
Coarse-to-Fine Vision Transformer
Vision Transformers (ViT) have made many breakthroughs in computer visio...
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02/15/2022
Pruning Networks with Cross-Layer Ranking k-Reciprocal Nearest Filters
This paper focuses on filter-level network pruning. A novel pruning meth...
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01/30/2022
Optimizing Gradient-driven Criteria in Network Sparsity: Gradient is All You Need
Network sparsity receives popularity mostly due to its capability to red...
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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...
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09/12/2021
Prioritized Subnet Sampling for Resource-Adaptive Supernet Training
A resource-adaptive supernet adjusts its subnets for inference to fit th...
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09/09/2021
Fine-grained Data Distribution Alignment for Post-Training Quantization
While post-training quantization receives popularity mostly due to its e...
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07/14/2021
Training Compact CNNs for Image Classification using Dynamic-coded Filter Fusion
The mainstream approach for filter pruning is usually either to force a ...
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05/31/2021
1×N Block Pattern for Network Sparsity
Though network sparsity emerges as a promising direction to overcome the...
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04/24/2021
Carrying out CNN Channel Pruning in a White Box
Channel Pruning has been long adopted for compressing CNNs, which signif...
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04/18/2021
Lottery Jackpots Exist in Pre-trained Models
Network pruning is an effective approach to reduce network complexity wi...
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04/06/2021
Learnable Expansion-and-Compression Network for Few-shot Class-Incremental Learning
Few-shot class-incremental learning (FSCIL), which targets at continuous...
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03/26/2021
Distilling a Powerful Student Model via Online Knowledge Distillation
Existing online knowledge distillation approaches either adopt the stude...
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03/23/2021
ReCU: Reviving the Dead Weights in Binary Neural Networks
Binary neural networks (BNNs) have received increasing attention due to ...
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02/16/2021
SiMaN: Sign-to-Magnitude Network Binarization
Binary neural networks (BNNs) have attracted broad research interest due...
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01/20/2021
Non-Parametric Adaptive Network Pruning
Popular network pruning algorithms reduce redundant information by optim...
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12/01/2020
Fast Class-wise Updating for Online Hashing
Online image hashing has received increasing research attention recently...
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11/17/2020
Learning Efficient GANs via Differentiable Masks and co-Attention Distillation
Generative Adversarial Networks (GANs) have been widely-used in image tr...
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09/28/2020
Rotated Binary Neural Network
Binary Neural Network (BNN) shows its predominance in reducing the compl...
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02/24/2020
HRank: Filter Pruning using High-Rank Feature Map
Neural network pruning offers a promising prospect to facilitate deployi...
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01/23/2020
Channel Pruning via Automatic Structure Search
Channel pruning is among the predominant approaches to compress deep neu...
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01/23/2020
Filter Sketch for Network Pruning
In this paper, we propose a novel network pruning approach by informatio...
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10/21/2019
Hadamard Codebook Based Deep Hashing
As an approximate nearest neighbor search technique, hashing has been wi...
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05/31/2019
Supervised Online Hashing via Similarity Distribution Learning
Online hashing has attracted extensive research attention when facing st...
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05/11/2019
Hadamard Matrix Guided Online Hashing
Online image hashing has received increasing research attention recently...
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04/28/2019
