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We focus on the foundational task of Scene Staging: given a reference scene image and a text condition specifying an actor category to be generated in the scene and its spatial relation to the scene, the goal is to synthesize an output…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Cong Xie , Che Wang , Yan Zhang , Ruiqi Yu , Han Zou , Zheng Pan , Zhenpeng Zhan

Monocular visual SLAM enables 3D reconstruction from internet video and autonomous navigation on resource-constrained platforms, yet suffers from scale drift, i.e., the gradual divergence of estimated scale over long sequences. Existing…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Yuchen Wu , Jiahe Li , Xiaohan Yu , Lina Yu , Jin Zheng , Xiao Bai

Currently, utilizing large language models to understand the 3D world is becoming popular. Yet existing 3D-aware LLMs act as black boxes: they output bounding boxes or textual answers without revealing how those decisions are made, and they…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Zhihao Yuan , Shuyi Jiang , Chun-Mei Feng , Yaolun Zhang , Shuguang Cui , Zhen Li , Na Zhao

For artistic applications, video generation requires fine-grained control over both performance and cinematography, i.e., the actor's motion and the camera trajectory. We present ActCam, a zero-shot method for video generation that jointly…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Omar El Khalifi , Thomas Rossi , Oscar Fossey , Thibault Fouque , Ulysse Mizrahi , Philip Torr , Ivan Laptev , Fabio Pizzati , Baptiste Bellot-Gurlet

Capturing and labeling real-world 3D data is laborious and time-consuming, which makes it costly to train strong 3D models. To address this issue, recent works present a simple method by generating randomized 3D scenes without simulation…

Computer Vision and Pattern Recognition · Computer Science 2023-08-08 Lanxiao Li , Michael Heizmann

3D Semantic Scene Completion (SSC) provides comprehensive scene geometry and semantics for autonomous driving perception, which is crucial for enabling accurate and reliable decision-making. However, existing SSC methods are limited to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Meng Wang , Fan Wu , Ruihui Li , Yunchuan Qin , Zhuo Tang , Kenli Li

We propose a decoupled 3D scene generation framework called SceneMaker in this work. Due to the lack of sufficient open-set de-occlusion and pose estimation priors, existing methods struggle to simultaneously produce high-quality geometry…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Yukai Shi , Weiyu Li , Zihao Wang , Hongyang Li , Xingyu Chen , Ping Tan , Lei Zhang

Recent advances in 4D generation mainly focus on generating 4D content by distilling pre-trained text or single-view image-conditioned models. It is inconvenient for them to take advantage of various off-the-shelf 3D assets with multi-view…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Yanqin Jiang , Chaohui Yu , Chenjie Cao , Fan Wang , Weiming Hu , Jin Gao

3D scene generation has quickly become a challenging new research direction, fueled by consistent improvements of 2D generative diffusion models. Most prior work in this area generates scenes by iteratively stitching newly generated frames…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Paul Engstler , Andrea Vedaldi , Iro Laina , Christian Rupprecht

3D scene understanding spans reasoning about free space, object grounding, hypothetical object insertions, complex geometric relationships, and integrating all of these with external tools and data sources. Existing 3D understanding methods…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Sagar Bharadwaj , Ziyong Ma , Anurag Ghosh , Srinivasan Seshan , Anthony Rowe

Achieving truly practical dynamic 3D reconstruction requires online operation, global pose and map consistency, detailed appearance modeling, and the flexibility to handle both RGB and RGB-D inputs. However, existing SLAM methods typically…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Shi Chen , Erik Sandström , Sandro Lombardi , Siyuan Li , Martin R. Oswald

The problem of generating a perpetual dynamic scene from a single view is an important problem with widespread applications in augmented and virtual reality, and robotics. However, since dynamic scenes regularly change over time, a key…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Fengrui Tian , Tianjiao Ding , Jinqi Luo , Hancheng Min , René Vidal

We introduce \textit{WonderVerse}, a simple but effective framework for generating extendable 3D scenes. Unlike existing methods that rely on iterative depth estimation and image inpainting, often leading to geometric distortions and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Hao Feng , Zhi Zuo , Jia-Hui Pan , Ka-Hei Hui , Qi Dou , Jingyu Hu , Zhengzhe Liu

We present SpaceTimePilot, a video diffusion model that disentangles space and time for controllable generative rendering. Given a monocular video, SpaceTimePilot can independently alter the camera viewpoint and the motion sequence within…

Computer Vision and Pattern Recognition · Computer Science 2026-01-01 Zhening Huang , Hyeonho Jeong , Xuelin Chen , Yulia Gryaditskaya , Tuanfeng Y. Wang , Joan Lasenby , Chun-Hao Huang

In this paper, we consider a novel and practical case for talking face video generation. Specifically, we focus on the scenarios involving multi-people interactions, where the talking context, such as audience or surroundings, is present.…

Computer Vision and Pattern Recognition · Computer Science 2024-02-29 Meidai Xuanyuan , Yuwang Wang , Honglei Guo , Qionghai Dai

Recent advances in 3D scene reconstruction and 4D human animation have broadened adoption, but integrating the two remains difficult. Key challenges include placing humans at plausible locations and scales without interpenetration, aligning…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Qingyang Liu , Bingjie Gao , Weiheng Huang , Jun Zhang , Zhongqian Sun , Yang Wei , Fengrui Liu , Zelin Peng , Qianli Ma , Shuai Yang , Zhaohe Liao , Haonan Zhao , Li Niu

A natural approach to generative modeling of videos is to represent them as a composition of moving objects. Recent works model a set of 2D sprites over a slowly-varying background, but without considering the underlying 3D scene that gives…

Computer Vision and Pattern Recognition · Computer Science 2021-03-26 Paul Henderson , Christoph H. Lampert

A comprehensive semantic understanding of a scene is important for many applications - but in what space should diverse semantic information (e.g., objects, scene categories, material types, texture, etc.) be grounded and what should be its…

Computer Vision and Pattern Recognition · Computer Science 2019-10-08 Iro Armeni , Zhi-Yang He , JunYoung Gwak , Amir R. Zamir , Martin Fischer , Jitendra Malik , Silvio Savarese

We introduce SceneScript, a method that directly produces full scene models as a sequence of structured language commands using an autoregressive, token-based approach. Our proposed scene representation is inspired by recent successes in…

Designing complex 3D scenes has been a tedious, manual process requiring domain expertise. Emerging text-to-3D generative models show great promise for making this task more intuitive, but existing approaches are limited to object-level…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Ryan Po , Gordon Wetzstein