2024 Poster "image generation" Papers
27 papers found
A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models
Sebastian Gregor Gruber, Florian Buettner
Accelerating Parallel Sampling of Diffusion Models
Zhiwei Tang, Jiasheng Tang, Hao Luo et al.
ArtWhisperer: A Dataset for Characterizing Human-AI Interactions in Artistic Creations
Kailas Vodrahalli, James Zou
Auto-GAS: Automated Proxy Discovery for Training-free Generative Architecture Search
Lujun Li, Haosen SUN, Shiwen Li et al.
Characteristic Guidance: Non-linear Correction for Diffusion Model at Large Guidance Scale
Candi Zheng, Yuan LAN
CipherDM: Secure Three-Party Inference for Diffusion Model Sampling
Xin Zhao, Xiaojun Chen, Xudong Chen et al.
Completing Visual Objects via Bridging Generation and Segmentation
Xiang Li, Yinpeng Chen, Chung-Ching Lin et al.
Critical windows: non-asymptotic theory for feature emergence in diffusion models
Marvin Li, Sitan Chen
Directly Denoising Diffusion Models
Dan Zhang, Jingjing Wang, Feng Luo
Feedback Efficient Online Fine-Tuning of Diffusion Models
Masatoshi Uehara, Yulai Zhao, Kevin Black et al.
Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations
Justin Deschenaux, Igor Krawczuk, Grigorios Chrysos et al.
Kepler codebook
Junrong Lian, Ziyue Dong, Pengxu Wei et al.
LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging
Jinuk Kim, Marwa El Halabi, Mingi Ji et al.
LLMGA: Multimodal Large Language Model based Generation Assistant
Bin Xia, Shiyin Wang, Yingfan Tao et al.
MS$^3$D: A RG Flow-Based Regularization for GAN Training with Limited Data
Jian Wang, Xin Lan, Yuxin Tian et al.
Neural Diffusion Models
Grigory Bartosh, Dmitry Vetrov, Christian Andersson Naesseth
On the Trajectory Regularity of ODE-based Diffusion Sampling
Defang Chen, Zhenyu Zhou, Can Wang et al.
Quantum Implicit Neural Representations
Jiaming Zhao, Wenbo Qiao, Peng Zhang et al.
ReGround: Improving Textual and Spatial Grounding at No Cost
Phillip (Yuseung) Lee, Minhyuk Sung
Scalable Wasserstein Gradient Flow for Generative Modeling through Unbalanced Optimal Transport
Jaemoo Choi, Jaewoong Choi, Myungjoo Kang
ShoeModel: Learning to Wear on the User-specified Shoes via Diffusion Model
Wenyu Li, Binghui Chen, Yifeng Geng et al.
Switch Diffusion Transformer: Synergizing Denoising Tasks with Sparse Mixture-of-Experts
Byeongjun Park, Hyojun Go, Jin-Young Kim et al.
The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling
Jiajun Ma, Shuchen Xue, Tianyang Hu et al.
Trainable Highly-expressive Activation Functions
Irit Chelly, Shahaf Finder, Shira Ifergane et al.
Understanding Diffusion Models by Feynman's Path Integral
Yuji Hirono, Akinori Tanaka, Kenji Fukushima
Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
Kaiwen Xue, Yuhao Zhou, Shen Nie et al.
Wear-Any-Way: Manipulable Virtual Try-on via Sparse Correspondence Alignment
Mengting Chen, Xi Chen, Zhonghua Zhai et al.