2 citations · 6 across the 32 of their papers we have counts for
8 papers · 1 filter
Inpaint4DNeRF: Promptable Spatio-Temporal NeRF Inpainting with Generative Diffusion Models
Han Jiang, Haosen Sun, Ruoxuan Li +2
Current Neural Radiance Fields (NeRF) can generate photorealistic novel views. For editing 3D scenes represented by NeRF, with the advent of generative models, this paper proposes…
Prompt2NeRF-PIL: Fast NeRF Generation via Pretrained Implicit Latent
Jianmeng Liu, Yuyao Zhang, Zeyuan Meng +2
This paper explores promptable NeRF generation (e.g., text prompt or single image prompt) for direct conditioning and fast generation of NeRF parameters for the underlying 3D scene…
Stable Segment Anything Model
Qi Fan, Xin Tao, Lei Ke +6
The Segment Anything Model (SAM) achieves remarkable promptable segmentation given high-quality prompts which, however, often require good skills to specify. To make SAM robust to…
DragVideo: Interactive Drag-style Video Editing
Yufan Deng, Ruida Wang, Yuhao Zhang +2
Video generation models have shown their superior ability to generate photo-realistic video. However, how to accurately control (or edit) the video remains a formidable challenge.…
SANeRF-HQ: Segment Anything for NeRF in High Quality
Yichen Liu, Benran Hu, Chi-Keung Tang +1
Recently, the Segment Anything Model (SAM) has showcased remarkable capabilities of zero-shot segmentation, while NeRF (Neural Radiance Fields) has gained popularity as a method fo…
C3Net: Compound Conditioned ControlNet for Multimodal Content Generation
Juntao Zhang, Yuehuai Liu, Yu-Wing Tai +1
We present Compound Conditioned ControlNet, C3Net, a novel generative neural architecture taking conditions from multiple modalities and synthesizing multimodal contents simultaneo…
InceptionHuman: Controllable Prompt-to-NeRF for Photorealistic 3D Human Generation
Shiu-hong Kao, Xinhang Liu, Yu-Wing Tai +1
This paper presents InceptionHuman, a prompt-to-NeRF framework that allows easy control via a combination of prompts in different modalities (e.g., text, poses, edge, segmentation…
EgoPCA: A New Framework for Egocentric Hand-Object Interaction Understanding
Yue Xu, Yong-Lu Li, Zhemin Huang +4
With the surge in attention to Egocentric Hand-Object Interaction (Ego-HOI), large-scale datasets such as Ego4D and EPIC-KITCHENS have been proposed. However, most current research…