activity
20192026
most citedPANet: Few-Shot Image Semantic Segmentation with Prototype Alignment

132 citations · 325 across the 36 of their papers we have counts for

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Showing 2023Show all

13 papers · 1 filter

cs.CV2023★ 6 cited

SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process

Mengyu Wang, Henghui Ding, Jun Hao Liew +3

In this paper, we explore a principal way to enhance the quality of object masks produced by different segmentation models. We propose a model-agnostic solution called SegRefiner,…

cs.CV2023★ 1 cited

Towards Accurate Guided Diffusion Sampling through Symplectic Adjoint Method

Jiachun Pan, Hanshu Yan, Jun Hao Liew +2

Training-free guided sampling in diffusion models leverages off-the-shelf pre-trained networks, such as an aesthetic evaluation model, to guide the generation process. Current trai…

cs.GR2023★ 1 cited

AvatarStudio: High-fidelity and Animatable 3D Avatar Creation from Text

Jianfeng Zhang, Xuanmeng Zhang, Huichao Zhang +4

We study the problem of creating high-fidelity and animatable 3D avatars from only textual descriptions. Existing text-to-avatar methods are either limited to static avatars which…

cs.CV2023★ 7 cited

MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model

Zhongcong Xu, Jianfeng Zhang, Jun Hao Liew +5

This paper studies the human image animation task, which aims to generate a video of a certain reference identity following a particular motion sequence. Existing animation works t…

cs.CV2023★ 2 cited

XAGen: 3D Expressive Human Avatars Generation

Zhongcong Xu, Jianfeng Zhang, Jun Hao Liew +2

Recent advances in 3D-aware GAN models have enabled the generation of realistic and controllable human body images. However, existing methods focus on the control of major body joi…

cs.CV2023★ 3 cited

MagicProp: Diffusion-based Video Editing via Motion-aware Appearance Propagation

Hanshu Yan, Jun Hao Liew, Long Mai +2

This paper addresses the issue of modifying the visual appearance of videos while preserving their motion. A novel framework, named MagicProp, is proposed, which disentangles the v…

cs.CV2023★ 11 cited

MagicEdit: High-Fidelity and Temporally Coherent Video Editing

Jun Hao Liew, Hanshu Yan, Jianfeng Zhang +2

In this report, we present MagicEdit, a surprisingly simple yet effective solution to the text-guided video editing task. We found that high-fidelity and temporally coherent video-…

cs.GR2023★ 5 cited

MagicAvatar: Multimodal Avatar Generation and Animation

Jianfeng Zhang, Hanshu Yan, Zhongcong Xu +2

This report presents MagicAvatar, a framework for multimodal video generation and animation of human avatars. Unlike most existing methods that generate avatar-centric videos direc…

cs.CV2023

AdjointDPM: Adjoint Sensitivity Method for Gradient Backpropagation of Diffusion Probabilistic Models

Jiachun Pan, Jun Hao Liew, Vincent Y. F. Tan +2

Existing customization methods require access to multiple reference examples to align pre-trained diffusion probabilistic models (DPMs) with user-provided concepts. This paper aims…

cs.CV2023★ 15 cited

DragDiffusion: Harnessing Diffusion Models for Interactive Point-based Image Editing

Yujun Shi, Chuhui Xue, Jun Hao Liew +5

Accurate and controllable image editing is a challenging task that has attracted significant attention recently. Notably, DragGAN is an interactive point-based image editing framew…

cs.CV2023★ 4 cited

Delving Deeper into Data Scaling in Masked Image Modeling

Cheng-Ze Lu, Xiaojie Jin, Qibin Hou +3

Understanding whether self-supervised learning methods can scale with unlimited data is crucial for training large-scale models. In this work, we conduct an empirical study on the…

cs.CV2023★ 1 cited

Associating Spatially-Consistent Grouping with Text-supervised Semantic Segmentation

Yabo Zhang, Zihao Wang, Jun Hao Liew +4

In this work, we investigate performing semantic segmentation solely through the training on image-sentence pairs. Due to the lack of dense annotations, existing text-supervised me…

cs.CV2023★ 2 cited

Global Knowledge Calibration for Fast Open-Vocabulary Segmentation

Kunyang Han, Yong Liu, Jun Hao Liew +8

Recent advancements in pre-trained vision-language models, such as CLIP, have enabled the segmentation of arbitrary concepts solely from textual inputs, a process commonly referred…