119 citations · 383 across the 47 of their papers we have counts for
47 papers
LAD-VF: LLM-Automatic Differentiation Enables Fine-Tuning-Free Robot Planning from Formal Methods Feedback
Yunhao Yang, Junyuan Hong, Gabriel Jacob Perin +4
Large language models (LLMs) can translate natural language instructions into executable action plans for robotics, autonomous driving, and other domains. Yet, deploying LLM-driven…
E3D-Bench: A Benchmark for End-to-End 3D Geometric Foundation Models
Wenyan Cong, Yiqing Liang, Yancheng Zhang +7
Spatial intelligence, encompassing 3D reconstruction, perception, and reasoning, is fundamental to applications such as robotics, aerial imaging, and extended reality. A key enable…
Steepest Descent Density Control for Compact 3D Gaussian Splatting
Peihao Wang, Yuehao Wang, Dilin Wang +8
3D Gaussian Splatting (3DGS) has emerged as a powerful technique for real-time, high-resolution novel view synthesis. By representing scenes as a mixture of Gaussian primitives, 3D…
Feature4X: Bridging Any Monocular Video to 4D Agentic AI with Versatile Gaussian Feature Fields
Shijie Zhou, Hui Ren, Yijia Weng +8
Recent advancements in 2D and multimodal models have achieved remarkable success by leveraging large-scale training on extensive datasets. However, extending these achievements to…
Can Test-Time Scaling Improve World Foundation Model?
Wenyan Cong, Hanqing Zhu, Peihao Wang +7
World foundation models, which simulate the physical world by predicting future states from current observations and inputs, have become central to many applications in physical in…
VideoLifter: Lifting Videos to 3D with Fast Hierarchical Stereo Alignment
Wenyan Cong, Hanqing Zhu, Kevin Wang +6
Efficiently reconstructing 3D scenes from monocular video remains a core challenge in computer vision, vital for applications in virtual reality, robotics, and scene understanding.…
Large Spatial Model: End-to-end Unposed Images to Semantic 3D
Zhiwen Fan, Jian Zhang, Wenyan Cong +10
Reconstructing and understanding 3D structures from a limited number of images is a well-established problem in computer vision. Traditional methods usually break this task into mu…
Expressive Gaussian Human Avatars from Monocular RGB Video
Hezhen Hu, Zhiwen Fan, Tianhao Wu +4
Nuanced expressiveness, particularly through fine-grained hand and facial expressions, is pivotal for enhancing the realism and vitality of digital human representations. In this w…
Learning Traffic Crashes as Language: Datasets, Benchmarks, and What-if Causal Analyses
Zhiwen Fan, Pu Wang, Yang Zhao +5
The increasing rate of road accidents worldwide results not only in significant loss of life but also imposes billions financial burdens on societies. Current research in traffic c…
4K4DGen: Panoramic 4D Generation at 4K Resolution
Renjie Li, Panwang Pan, Bangbang Yang +8
The blooming of virtual reality and augmented reality (VR/AR) technologies has driven an increasing demand for the creation of high-quality, immersive, and dynamic environments. Ho…
LLMGeo: Benchmarking Large Language Models on Image Geolocation In-the-wild
Zhiqiang Wang, Dejia Xu, Rana Muhammad Shahroz Khan +3
Image geolocation is a critical task in various image-understanding applications. However, existing methods often fail when analyzing challenging, in-the-wild images. Inspired by t…
DreamScene360: Unconstrained Text-to-3D Scene Generation with Panoramic Gaussian Splatting
Shijie Zhou, Zhiwen Fan, Dejia Xu +6
The increasing demand for virtual reality applications has highlighted the significance of crafting immersive 3D assets. We present a text-to-3D 360 scene generation pipe…
MM3DGS SLAM: Multi-modal 3D Gaussian Splatting for SLAM Using Vision, Depth, and Inertial Measurements
Lisong C. Sun, Neel P. Bhatt, Jonathan C. Liu +4
Simultaneous localization and mapping is essential for position tracking and scene understanding. 3D Gaussian-based map representations enable photorealistic reconstruction and rea…
Lift3D: Zero-Shot Lifting of Any 2D Vision Model to 3D
Mukund Varma T, Peihao Wang, Zhiwen Fan +3
In recent years, there has been an explosion of 2D vision models for numerous tasks such as semantic segmentation, style transfer or scene editing, enabled by large-scale 2D image…
InstantSplat: Sparse-view Gaussian Splatting in Seconds
Zhiwen Fan, Wenyan Cong, Kairun Wen +9
While neural 3D reconstruction has advanced substantially, its performance significantly degrades with sparse-view data, which limits its broader applicability, since SfM is often…
Taming Mode Collapse in Score Distillation for Text-to-3D Generation
Peihao Wang, Dejia Xu, Zhiwen Fan +8
Despite the remarkable performance of score distillation in text-to-3D generation, such techniques notoriously suffer from view inconsistency issues, also known as "Janus" artifact…
SteinDreamer: Variance Reduction for Text-to-3D Score Distillation via Stein Identity
Peihao Wang, Zhiwen Fan, Dejia Xu +8
Score distillation has emerged as one of the most prevalent approaches for text-to-3D asset synthesis. Essentially, score distillation updates 3D parameters by lifting and back-pro…
Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature Fields
Shijie Zhou, Haoran Chang, Sicheng Jiang +7
3D scene representations have gained immense popularity in recent years. Methods that use Neural Radiance fields are versatile for traditional tasks such as novel view synthesis. I…
FSGS: Real-Time Few-shot View Synthesis using Gaussian Splatting
Zehao Zhu, Zhiwen Fan, Yifan Jiang +1
Novel view synthesis from limited observations remains an important and persistent task. However, high efficiency in existing NeRF-based few-shot view synthesis is often compromise…
LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPS
Zhiwen Fan, Kevin Wang, Kairun Wen +3
Recent advances in real-time neural rendering using point-based techniques have enabled broader adoption of 3D representations. However, foundational approaches like 3D Gaussian Sp…
Pose-Free Generalizable Rendering Transformer
Zhiwen Fan, Panwang Pan, Peihao Wang +6
In the field of novel-view synthesis, the necessity of knowing camera poses (e.g., via Structure from Motion) before rendering has been a common practice. However, the consistent a…
Enhancing NeRF akin to Enhancing LLMs: Generalizable NeRF Transformer with Mixture-of-View-Experts
Wenyan Cong, Hanxue Liang, Peihao Wang +5
Cross-scene generalizable NeRF models, which can directly synthesize novel views of unseen scenes, have become a new spotlight of the NeRF field. Several existing attempts rely on…
INR-Arch: A Dataflow Architecture and Compiler for Arbitrary-Order Gradient Computations in Implicit Neural Representation Processing
Stefan Abi-Karam, Rishov Sarkar, Dejia Xu +3
An increasing number of researchers are finding use for nth-order gradient computations for a wide variety of applications, including graphics, meta-learning (MAML), scientific com…
Learning to Estimate 6DoF Pose from Limited Data: A Few-Shot, Generalizable Approach using RGB Images
Panwang Pan, Zhiwen Fan, Brandon Y. Feng +3
The accurate estimation of six degrees-of-freedom (6DoF) object poses is essential for many applications in robotics and augmented reality. However, existing methods for 6DoF pose…