Search Results for author:
Found 13 papers, 7 papers with code
Dynamic and Super-Personalized Media Ecosystem Driven by Generative AI: Unpredictable Plays Never Repeating The Same
This paper introduces a media service model that exploits artificial intelligence (AI) video generators at the receive end.
KOALA: Self-Attention Matters in Knowledge Distillation of Latent Diffusion Models for Memory-Efficient and Fast Image Synthesis
We hope that due to its balanced speed-performance tradeoff, our KOALA models can serve as a cost-effective alternative to SDXL in resource-constrained environments.
EVEREST: Efficient Masked Video Autoencoder by Removing Redundant Spatiotemporal Tokens
Masked Video Autoencoder (MVA) approaches have demonstrated their potential by significantly outperforming previous video representation learning methods.
Ranked #1 on
Object State Change Classification
on Ego4D
Object State Change Classification
Object State Change Classification on Ego4D
+4
Exploring The Role of Mean Teachers in Self-supervised Masked Auto-Encoders
Masked image modeling (MIM) has become a popular strategy for self-supervised learning~(SSL) of visual representations with Vision Transformers.
MPViT: Multi-Path Vision Transformer for Dense Prediction
While Convolutional Neural Networks (CNNs) have been the dominant architectures for such tasks, recently introduced Vision Transformers (ViTs) aim to replace them as a backbone.
Ranked #38 on
Instance Segmentation
on COCO minival
Diverse Temporal Aggregation and Depthwise Spatiotemporal Factorization for Efficient Video Classification
By using the proposed temporal modeling method (T-OSA), and the efficient factorized component (D(2+1)D), we construct two types of VoV3D networks, VoV3D-M and VoV3D-L.
Ranked #29 on
Action Recognition
on Something-Something V1
(using extra training data)
Adversarial Training with Stochastic Weight Average
Moreover, we further improved SWA to be adequate to adversarial training.
Localization Uncertainty Estimation for Anchor-Free Object Detection
To tackle these limitations, we propose a new localization uncertainty estimation method called UAD for anchor-free object detection.
Ranked #116 on
Object Detection
on COCO test-dev
CenterMask: Real-Time Anchor-Free Instance Segmentation
We propose a simple yet efficient anchor-free instance segmentation, called CenterMask, that adds a novel spatial attention-guided mask (SAG-Mask) branch to anchor-free one stage object detector (FCOS) in the same vein with Mask R-CNN.
CenterMask : Real-Time Anchor-Free Instance Segmentation
We hope that CenterMask and VoVNetV2 can serve as a solid baseline of real-time instance segmentation and backbone network for various vision tasks, respectively.
Ranked #1 on
Object Detection
on COCO test-dev
(Hardware Burden metric)
An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection
As DenseNet conserves intermediate features with diverse receptive fields by aggregating them with dense connection, it shows good performance on the object detection task.
Ranked #64 on
Instance Segmentation
on COCO test-dev
Rank of Experts: Detection Network Ensemble
The recent advances of convolutional detectors show impressive performance improvement for large scale object detection.
Wide-Residual-Inception Networks for Real-time Object Detection
Since convolutional neural network(CNN)models emerged, several tasks in computer vision have actively deployed CNN models for feature extraction.
