Poster Papers
24,624 papers found • Page 349 of 493
Conference
DaReNeRF: Direction-aware Representation for Dynamic Scenes
Ange Lou, Benjamin Planche, Zhongpai Gao et al.
DART: Implicit Doppler Tomography for Radar Novel View Synthesis
Tianshu Huang, John Miller, Akarsh Prabhakara et al.
Data Augmentation via Latent Diffusion for Saliency Prediction
Bahar Aydemir, Deblina Bhattacharjee, Tong Zhang et al.
Data Collection-free Masked Video Modeling
Yuchi Ishikawa, Masayoshi Kondo, Yoshimitsu Aoki
Data Debugging with Shapley Importance over Machine Learning Pipelines
Bojan Karlaš, David Dao, Matteo Interlandi et al.
Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality
Xuxi Chen, Yu Yang, Zhangyang Wang et al.
DataDream: Few-shot Guided Dataset Generation
Jae Myung Kim, Jessica Bader, Stephan Alaniz et al.
Data-efficient Large Vision Models through Sequential Autoregression
Zhiwei Hao, Jianyuan Guo, Chengcheng Wang et al.
Data-Efficient Learning via Clustering-Based Sensitivity Sampling: Foundation Models and Beyond
Kyriakos Axiotis, Vincent Cohen-Addad, Monika Henzinger et al.
Data-Efficient Molecular Generation with Hierarchical Textual Inversion
Seojin Kim, Jaehyun Nam, Sihyun Yu et al.
Data-Efficient Unsupervised Interpolation Without Any Intermediate Frame for 4D Medical Images
JungEun Kim, Hangyul Yoon, Geondo Park et al.
Data Engineering for Scaling Language Models to 128K Context
Yao Fu, Rameswar Panda, Xinyao Niu et al.
Data Filtering Networks
Alex Fang, Albin Madappally Jose, Amit Jain et al.
Data-free Distillation of Diffusion Models with Bootstrapping
Jiatao Gu, Chen Wang, Shuangfei Zhai et al.
Data-free Neural Representation Compression with Riemannian Neural Dynamics
Zhengqi Pei, Anran Zhang, Shuhui Wang et al.
Data-Free Quantization via Pseudo-label Filtering
Chunxiao Fan, Ziqi Wang, Dan Guo et al.
DataFreeShield: Defending Adversarial Attacks without Training Data
Hyeyoon Lee, Kanghyun Choi, Dain Kwon et al.
Data-independent Module-aware Pruning for Hierarchical Vision Transformers
Yang He, Joey Tianyi Zhou
DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models
Yongchan Kwon, Eric Wu, Kevin Wu et al.
Data Overfitting for On-Device Super-Resolution with Dynamic Algorithm and Compiler Co-Design
Li, zhihao shu, Jie Ji et al.
Data Poisoning Attacks against Conformal Prediction
Yangyi Li, Aobo Chen, Wei Qian et al.
Data Poisoning based Backdoor Attacks to Contrastive Learning
Jinghuai Zhang, Hongbin Liu, Jinyuan Jia et al.
Data Poisoning Quantization Backdoor Attack
Tran Huynh, Anh Tran, Khoa Doan et al.
Dataset Distillation by Automatic Training Trajectories
Dai Liu, Jindong Gu, Hu Cao et al.
Dataset Enhancement with Instance-Level Augmentations
Orest Kupyn, Christian Rupprecht
Dataset Growth
Ziheng Qin, zhaopan xu, YuKun Zhou et al.
DatasetNeRF: Efficient 3D-aware Data Factory with Generative Radiance Fields
Yu Chi, Fangneng Zhan, Sibo Wu et al.
Dataset Quantization with Active Learning based Adaptive Sampling
Zhenghao Zhao, Yuzhang Shang, Junyi Wu et al.
Data-to-Model Distillation: Data-Efficient Learning Framework
Ahmad Sajedi, Samir Khaki, Lucy Z. Liu et al.
Data Valuation and Detections in Federated Learning
Wenqian Li, Shuran Fu, Fengrui Zhang et al.
DATENeRF: Depth-Aware Text-based Editing of NeRFs
Sara Rojas Martinez, Julien Philip, Kai Zhang et al.
DATS: Difficulty-Aware Task Sampler for Meta-Learning Physics-Informed Neural Networks
Maryam Toloubidokhti, Yubo Ye, Ryan Missel et al.
DAVE - A Detect-and-Verify Paradigm for Low-Shot Counting
Jer Pelhan, Alan Lukezic, Vitjan Zavrtanik et al.
Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation
Jaemin Cho, Yushi Hu, Jason Baldridge et al.
Day-Night Cross-domain Vehicle Re-identification
Hongchao Li, Jingong Chen, AIHUA ZHENG et al.
DCDM: Diffusion-Conditioned-Diffusion Model for Scene Text Image Super-Resolution
Shrey Singh, Prateek Keserwani, Masakazu Iwamura et al.
DC-Solver: Improving Predictor-Corrector Diffusion Sampler via Dynamic Compensation
Wenliang Zhao, Haolin Wang, Jie Zhou et al.
DDMI: Domain-agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representations
Dogyun Park, Sihyeon Kim, Sojin Lee et al.
DEAL: Disentangle and Localize Concept-level Explanations for VLMs
Tang Li, Mengmeng Ma, Xi Peng
Dealing With Unbounded Gradients in Stochastic Saddle-point Optimization
Gergely Neu, Nneka Okolo
Debating with More Persuasive LLMs Leads to More Truthful Answers
Akbir Khan, John Hughes, Dan Valentine et al.
Debiased Distribution Compression
Lingxiao Li, Raaz Dwivedi, Lester Mackey
Debiased Offline Representation Learning for Fast Online Adaptation in Non-stationary Dynamics
Xinyu Zhang, Wenjie Qiu, Yi-Chen Li et al.
Debiasing Algorithm through Model Adaptation
Tomasz Limisiewicz, David Mareček, Tomáš Musil
Debiasing Attention Mechanism in Transformer without Demographics
Shenyu Lu, Yipei Wang, Xiaoqian Wang
Debiasing surgeon: fantastic weights and how to find them
Remi Nahon, Ivan Luiz De Moura Matos, Van-Tam Nguyen et al.
Deblur e-NeRF: NeRF from Motion-Blurred Events under High-speed or Low-light Conditions
Weng Fei Low, Gim Hee Lee
Deblurring 3D Gaussian Splatting
Byeonghyeon Lee, Howoong Lee, Xiangyu Sun et al.
DECap: Towards Generalized Explicit Caption Editing via Diffusion Mechanism
Zhen Wang, Xinyun Jiang, Jun Xiao et al.
DecentNeRFs: Decentralized Neural Radiance Fields from Crowdsourced Images
Zaid Tasneem, Akshat Dave, Abhishek Singh et al.