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20212026
most cited3D-Aware Video Generation

8 citations · 12 across the 14 of their papers we have counts for

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Showing 2024 · cs.CVShow all

5 papers · 2 filters

cs.CV2024

AC3D: Analyzing and Improving 3D Camera Control in Video Diffusion Transformers

Sherwin Bahmani, Ivan Skorokhodov, Guocheng Qian +5

Numerous works have recently integrated 3D camera control into foundational text-to-video models, but the resulting camera control is often imprecise, and video generation quality…

cs.CV2024

SG-I2V: Self-Guided Trajectory Control in Image-to-Video Generation

Koichi Namekata, Sherwin Bahmani, Ziyi Wu +3

Methods for image-to-video generation have achieved impressive, photo-realistic quality. However, adjusting specific elements in generated videos, such as object motion or camera m…

cs.CV2024

GStex: Per-Primitive Texturing of 2D Gaussian Splatting for Decoupled Appearance and Geometry Modeling

Victor Rong, Jingxiang Chen, Sherwin Bahmani +2

Gaussian splatting has demonstrated excellent performance for view synthesis and scene reconstruction. The representation achieves photorealistic quality by optimizing the position…

cs.CV2024

VD3D: Taming Large Video Diffusion Transformers for 3D Camera Control

Sherwin Bahmani, Ivan Skorokhodov, Aliaksandr Siarohin +9

Modern text-to-video synthesis models demonstrate coherent, photorealistic generation of complex videos from a text description. However, most existing models lack fine-grained con…

cs.CV2024

TC4D: Trajectory-Conditioned Text-to-4D Generation

Sherwin Bahmani, Xian Liu, Wang Yifan +9

Recent techniques for text-to-4D generation synthesize dynamic 3D scenes using supervision from pre-trained text-to-video models. However, existing representations for motion, such…