activity
20232026
most citedEfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything

15 citations · 19 across the 18 of their papers we have counts for

collaborators

20 papers

cs.CV2026

CoVeR: Coverage-Based Token Pruning for Multi-View 3D Reasoning in VLMs

Nhat-Tan Bui, Varshini Elangovan, Arun Reddy Anugu +7

Representing a 3D scene as multi-view images allows 2D VLMs to reason in 3D by reusing priors from pre-training, sidestepping the scarcity of annotated 3D data. However, it produce…

cs.CV2026

OpenLongTail: Generative Scaling of Long-Tail Driving Data

Lulin Liu, Nuo Chen, Yan Wang +15

Scaling robust driving policies is fundamentally bottlenecked by the scarcity of edge cases in curated datasets. While the real world continuously captures these critical events, s…

cs.GR2026

OmniFaceRig: Fully Automatic Inner-Mouth-Aware Face Rigging Across Diverse 3D Character Topologies

Chao Wang, Guangyao Ma, John Doublestein +10

Facial rigging - creating FACS-based blendshapes together with inner-mouth geometry (teeth, gums, and tongue) - remains a major bottleneck in 3D character production. Existing pipe…

cs.GR2026

AssetGen: Deployable 3D Asset Generation at Interactive Speed

Dilin Wang, Xiaoyu Xiang, Kihyuk Sohn +14

While 3D generation is progressing rapidly, recent work has often focused on obtaining high-resolution assets, leaving user experience and deployability as afterthoughts. We presen…

cs.CV2026

Co-generation of Layout and Shape from Text via Autoregressive 3D Diffusion

Zhenggang Tang, Yuehao Wang, Yuchen Fan +9

Recent text-to-scene generation approaches largely reduced the manual efforts required to create 3D scenes. However, their focus is either to generate a scene layout or to generate…

cs.CV2025

DynamicVerse: A Physically-Aware Multimodal Framework for 4D World Modeling

Kairun Wen, Yuzhi Huang, Runyu Chen +16

Understanding the dynamic physical world, characterized by its evolving 3D structure, real-world motion, and semantic content with textual descriptions, is crucial for human-agent…

cs.CV2025

WorldGen: From Text to Traversable and Interactive 3D Worlds

Dilin Wang, Hyunyoung Jung, Tom Monnier +22

We introduce WorldGen, a system that enables the automatic creation of large-scale, interactive 3D worlds directly from text prompts. Our approach transforms natural language descr…

cs.CV2025

AutoPartGen: Autogressive 3D Part Generation and Discovery

Minghao Chen, Jianyuan Wang, Roman Shapovalov +6

We introduce AutoPartGen, a model that generates objects composed of 3D parts in an autoregressive manner. This model can take as input an image of an object, 2D masks of the objec…

cs.CV2025

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…

cs.CV2025

VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction

Zhiwen Fan, Jian Zhang, Renjie Li +15

The rapid advancement of Large Multimodal Models (LMMs) for 2D images and videos has motivated extending these models to understand 3D scenes, aiming for human-like visual-spatial…

cs.CV2025

LIRM: Large Inverse Rendering Model for Progressive Reconstruction of Shape, Materials and View-dependent Radiance Fields

Zhengqin Li, Dilin Wang, Ka Chen +11

We present Large Inverse Rendering Model (LIRM), a transformer architecture that jointly reconstructs high-quality shape, materials, and radiance fields with view-dependent effects…

cs.CV2025

UVGS: Reimagining Unstructured 3D Gaussian Splatting using UV Mapping

Aashish Rai, Dilin Wang, Mihir Jain +4

3D Gaussian Splatting (3DGS) has demonstrated superior quality in modeling 3D objects and scenes. However, generating 3DGS remains challenging due to their discrete, unstructured,…

cs.CV2025

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.…

cs.CV2024

MV-DUSt3R+: Single-Stage Scene Reconstruction from Sparse Views In 2 Seconds

Zhenggang Tang, Yuchen Fan, Dilin Wang +4

Recent sparse multi-view scene reconstruction advances like DUSt3R and MASt3R no longer require camera calibration and camera pose estimation. However, they only process a pair of…

cs.CV2024

3D Mesh Editing using Masked LRMs

Will Gao, Dilin Wang, Yuchen Fan +6

We present a novel approach to shape editing, building on recent progress in 3D reconstruction from multi-view images. We formulate shape editing as a conditional reconstruction pr…

cs.CV2024

MVDiffusion++: A Dense High-resolution Multi-view Diffusion Model for Single or Sparse-view 3D Object Reconstruction

Shitao Tang, Jiacheng Chen, Dilin Wang +6

This paper presents a neural architecture MVDiffusion++ for 3D object reconstruction that synthesizes dense and high-resolution views of an object given one or a few images without…

cs.CV2024★ 1 cited

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…

cs.CV2024★ 3 cited

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…

cs.CV2023★ 15 cited

EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything

Yunyang Xiong, Bala Varadarajan, Lemeng Wu +9

Segment Anything Model (SAM) has emerged as a powerful tool for numerous vision applications. A key component that drives the impressive performance for zero-shot transfer and high…

cs.CV2023

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…