Poster "computational efficiency" Papers
158 papers found • Page 3 of 4
Conference
Context-Guided Spatial Feature Reconstruction for Efficient Semantic Segmentation
Zhenliang Ni, Xinghao Chen, Yingjie Zhai et al.
CrossGET: Cross-Guided Ensemble of Tokens for Accelerating Vision-Language Transformers
Dachuan Shi, Chaofan Tao, Anyi Rao et al.
Deep Fusion: Efficient Network Training via Pre-trained Initializations
Hanna Mazzawi, Xavi Gonzalvo, Michael Wunder et al.
Differentially Private Bias-Term Fine-tuning of Foundation Models
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha et al.
Distilled Datamodel with Reverse Gradient Matching
Jingwen Ye, Ruonan Yu, Songhua Liu et al.
Distilling Semantic Priors from SAM to Efficient Image Restoration Models
Quan Zhang, Xiaoyu Liu, Wei Li et al.
DistiLLM: Towards Streamlined Distillation for Large Language Models
Jongwoo Ko, Sungnyun Kim, Tianyi Chen et al.
Distributed Semantic Segmentation with Efficient Joint Source and Task Decoding
Danish Nazir, Timo Bartels, Jan Piewek et al.
Do Efficient Transformers Really Save Computation?
Kai Yang, Jan Ackermann, Zhenyu He et al.
Dynamic Data Selection for Efficient SSL via Coarse-to-Fine Refinement
Aditay Tripathi, Pradeep Shenoy, Anirban Chakraborty
Efficient Cascaded Multiscale Adaptive Network for Image Restoration
Yichen Zhou, Pan Zhou, Teck Khim Ng
Enabling Uncertainty Estimation in Iterative Neural Networks
Nikita Durasov, Doruk Oner, Jonathan Donier et al.
Enhancing Storage and Computational Efficiency in Federated Multimodal Learning for Large-Scale Models
Zixin Zhang, Fan Qi, Changsheng Xu
Enhancing Vision Transformer: Amplifying Non-Linearity in Feedforward Network Module
Yixing Xu, Chao Li, Dong Li et al.
Evaluation of Test-Time Adaptation Under Computational Time Constraints
Motasem Alfarra, Hani Itani, Alejandro Pardo et al.
Fast Decision Boundary based Out-of-Distribution Detector
Litian Liu, Yao Qin
FMBoost: Boosting Latent Diffusion with Flow Matching
Johannes Schusterbauer-Fischer, Ming Gui, Pingchuan Ma et al.
FRDiff : Feature Reuse for Universal Training-free Acceleration of Diffusion Models
Junhyuk So, Jungwon Lee, Eunhyeok Park
Frugal 3D Point Cloud Model Training via Progressive Near Point Filtering and Fused Aggregation
Donghyun Lee, Yejin Lee, Jae W. Lee et al.
Grid-Attention: Enhancing Computational Efficiency of Large Vision Models without Fine-Tuning
Pengyu Li, Biao Wang, Tianchu Guo et al.
Grid Diffusion Models for Text-to-Video Generation
Taegyeong Lee, Soyeong Kwon, Taehwan Kim
Headless Language Models: Learning without Predicting with Contrastive Weight Tying
Nathan Godey, Éric Clergerie, Benoît Sagot
Hierarchical Separable Video Transformer for Snapshot Compressive Imaging
Ping Wang, Yulun Zhang, Lishun Wang et al.
HPE-Li: WiFi-enabled Lightweight Dual Selective Kernel Convolution for Human Pose Estimation
Gian Toan D., Tien Dac Lai, Thien Van Luong et al.
In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering
Sheng Liu, Haotian Ye, Lei Xing et al.
Learning Causal Dynamics Models in Object-Oriented Environments
Zhongwei Yu, Jingqing Ruan, Dengpeng Xing
LiteSAM is Actually what you Need for segment Everything
Jianhai Fu, Yuanjie Yu, Ningchuan Li et al.
Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models
Gianni Franchi, Olivier Laurent, Maxence Leguéry et al.
Mixture of Efficient Diffusion Experts Through Automatic Interval and Sub-Network Selection
Alireza Ganjdanesh, Yan Kang, Yuchen Liu et al.
Object-Centric Diffusion for Efficient Video Editing
Kumara Kahatapitiya, Adil Karjauv, Davide Abati et al.
ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models
Dongha Kim, Jaesung Hwang, Jongjin Lee et al.
One-stage Prompt-based Continual Learning
Youngeun Kim, YUHANG LI, Priyadarshini Panda
Optimizing Diffusion Models for Joint Trajectory Prediction and Controllable Generation
Yixiao Wang, Chen Tang, Lingfeng Sun et al.
Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty
Kaizhao Liu, Jose Blanchet, Lexing Ying et al.
Partially Stochastic Infinitely Deep Bayesian Neural Networks
Sergio Calvo Ordoñez, Matthieu Meunier, Francesco Piatti et al.
PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design
Alexandre Duval, Victor Schmidt, Santiago Miret et al.
Quantization-Friendly Winograd Transformations for Convolutional Neural Networks
Vladimir Protsenko, Vladimir Kryzhanovskiy, Alexander Filippov
Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency
Sudeep Salgia, Sattar Vakili, Qing Zhao
RegionDrag: Fast Region-Based Image Editing with Diffusion Models
Jingyi Lu, Xinghui Li, Kai Han
Removing Rows and Columns of Tokens in Vision Transformer enables Faster Dense Prediction without Retraining
Diwei Su, cheng fei, Jianxu Luo
Rethinking Diffusion Model for Multi-Contrast MRI Super-Resolution
Guangyuan Li, Chen Rao, Juncheng Mo et al.
Rethinking Video Deblurring with Wavelet-Aware Dynamic Transformer and Diffusion Model
chen rao, Guangyuan Li, Zehua Lan et al.
SAFNet: Selective Alignment Fusion Network for Efficient HDR Imaging
Lingtong Kong, Bo Li, Yike Xiong et al.
Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement
Xiuquan Hou, Meiqin Liu, Senlin Zhang et al.
Saliency strikes back: How filtering out high frequencies improves white-box explanations
Sabine Muzellec, Thomas FEL, Victor Boutin et al.
Scaling Laws for Fine-Grained Mixture of Experts
Jan Ludziejewski, Jakub Krajewski, Kamil Adamczewski et al.
ScanFormer: Referring Expression Comprehension by Iteratively Scanning
Wei Su, Peihan Miao, Huanzhang Dou et al.
See More Details: Efficient Image Super-Resolution by Experts Mining
Eduard Zamfir, Zongwei Wu, Nancy Mehta et al.
Self-Adapting Large Visual-Language Models to Edge Devices across Visual Modalities
Kaiwen Cai, ZheKai Duan, Gaowen Liu et al.
SMFANet: A Lightweight Self-Modulation Feature Aggregation Network for Efficient Image Super-Resolution
mingjun zheng, Long Sun, Jiangxin Dong et al.