3 citations · 14 across the 20 of their papers we have counts for
15 papers · 1 filter
DiffusionBench: On Holistic Evaluation of Diffusion Transformers
Xingjian Leng, Jaskirat Singh, Zhanhao Liang +5
Diffusion transformer (DiT) research on image generation has converged to a single evaluation setup: class-conditional generation on ImageNet. While methods improve the FID and rel…
Improved Baselines with Representation Autoencoders
Jaskirat Singh, Boyang Zheng, Zongze Wu +3
Representation Autoencoders (RAE) replace traditional VAE with pretrained vision encoders. In this paper, we systematically investigate several design choices and find three insigh…
What matters for Representation Alignment: Global Information or Spatial Structure?
Jaskirat Singh, Xingjian Leng, Zongze Wu +4
Representation alignment (REPA) guides generative training by distilling representations from a strong, pretrained vision encoder to intermediate diffusion features. We investigate…
Vec2Face+ for Face Dataset Generation
Haiyu Wu, Jaskirat Singh, Sicong Tian +2
When synthesizing identities as face recognition training data, it is generally believed that large inter-class separability and intra-class attribute variation are essential for s…
DiSA: Diffusion Step Annealing in Autoregressive Image Generation
Qinyu Zhao, Jaskirat Singh, Ming Xu +3
An increasing number of autoregressive models, such as MAR, FlowAR, xAR, and Harmon adopt diffusion sampling to improve the quality of image generation. However, this strategy lead…
REPA-E: Unlocking VAE for End-to-End Tuning with Latent Diffusion Transformers
Xingjian Leng, Jaskirat Singh, Yunzhong Hou +3
In this paper we tackle a fundamental question: "Can we train latent diffusion models together with the variational auto-encoder (VAE) tokenizer in an end-to-end manner?" Tradition…
Negative Token Merging: Image-based Adversarial Feature Guidance
Jaskirat Singh, Lindsey Li, Weijia Shi +7
Text-based adversarial guidance using a negative prompt has emerged as a widely adopted approach to steer diffusion models away from producing undesired concepts. While useful, per…
Vec2Face: Scaling Face Dataset Generation with Loosely Constrained Vectors
Haiyu Wu, Jaskirat Singh, Sicong Tian +2
This paper studies how to synthesize face images of non-existent persons, to create a dataset that allows effective training of face recognition (FR) models. Besides generating rea…
SmartMask: Context Aware High-Fidelity Mask Generation for Fine-grained Object Insertion and Layout Control
Jaskirat Singh, Jianming Zhang, Qing Liu +3
The field of generative image inpainting and object insertion has made significant progress with the recent advent of latent diffusion models. Utilizing a precise object mask can g…
Divide, Evaluate, and Refine: Evaluating and Improving Text-to-Image Alignment with Iterative VQA Feedback
Jaskirat Singh, Liang Zheng
The field of text-conditioned image generation has made unparalleled progress with the recent advent of latent diffusion models. While remarkable, as the complexity of given text i…
Probabilistic and Semantic Descriptions of Image Manifolds and Their Applications
Peter Tu, Zhaoyuan Yang, Richard Hartley +6
This paper begins with a description of methods for estimating image probability density functions that reflects the observation that such data is usually constrained to lie in res…
High-Fidelity Guided Image Synthesis with Latent Diffusion Models
Jaskirat Singh, Stephen Gould, Liang Zheng
Controllable image synthesis with user scribbles has gained huge public interest with the recent advent of text-conditioned latent diffusion models. The user scribbles control the…
Paint2Pix: Interactive Painting based Progressive Image Synthesis and Editing
Jaskirat Singh, Liang Zheng, Cameron Smith +1
Controllable image synthesis with user scribbles is a topic of keen interest in the computer vision community. In this paper, for the first time we study the problem of photorealis…
Intelli-Paint: Towards Developing Human-like Painting Agents
Jaskirat Singh, Cameron Smith, Jose Echevarria +1
The generation of well-designed artwork is often quite time-consuming and assumes a high degree of proficiency on part of the human painter. In order to facilitate the human painti…
Combining Semantic Guidance and Deep Reinforcement Learning For Generating Human Level Paintings
Jaskirat Singh, Liang Zheng
Generation of stroke-based non-photorealistic imagery, is an important problem in the computer vision community. As an endeavor in this direction, substantial recent research effor…