activity
20192024
most citedDisentangled Recurrent Wasserstein Autoencoder

16 citations · 42 across the 11 of their papers we have counts for

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9 papers · 1 filter

cs.CV20241 cited

Score-Guided Diffusion for 3D Human Recovery

Anastasis Stathopoulos, Ligong Han, Dimitris Metaxas

We present Score-Guided Human Mesh Recovery (ScoreHMR), an approach for solving inverse problems for 3D human pose and shape reconstruction. These inverse problems involve fitting…

cs.CV2023

Improving Tuning-Free Real Image Editing with Proximal Guidance

Ligong Han, Song Wen, Qi Chen +13

DDIM inversion has revealed the remarkable potential of real image editing within diffusion-based methods. However, the accuracy of DDIM reconstruction degrades as larger classifie…

cs.CV2023

Learning Articulated Shape with Keypoint Pseudo-labels from Web Images

Anastasis Stathopoulos, Georgios Pavlakos, Ligong Han +1

This paper shows that it is possible to learn models for monocular 3D reconstruction of articulated objects (e.g., horses, cows, sheep), using as few as 50-150 images labeled with…

cs.CV20231 cited

Constructive Assimilation: Boosting Contrastive Learning Performance through View Generation Strategies

Ligong Han, Seungwook Han, Shivchander Sudalairaj +8

Transformations based on domain expertise (expert transformations), such as random-resized-crop and color-jitter, have proven critical to the success of contrastive learning techni…

cs.CV202212 cited

Diffusion Guided Domain Adaptation of Image Generators

Kunpeng Song, Ligong Han, Bingchen Liu +2

Can a text-to-image diffusion model be used as a training objective for adapting a GAN generator to another domain? In this paper, we show that the classifier-free guidance can be…

cs.CV2022

Show Me What and Tell Me How: Video Synthesis via Multimodal Conditioning

Ligong Han, Jian Ren, Hsin-Ying Lee +5

Most methods for conditional video synthesis use a single modality as the condition. This comes with major limitations. For example, it is problematic for a model conditioned on an…