activity
20192026
most citedImage-driven discriminative and generative machine learning algorithms for establishing microstructure-processing relationships

50 citations · 61 across the 29 of their papers we have counts for

collaborators

34 papers

cs.CL2026

Muse Glimmer 30B: An On-Device Agentic Model

Arash Ebrahim Abtahizadeh, Muna Aghamelu, Adil Ahmed +327

We introduce Muse Glimmer, an open-source 30B parameter causal language model with perception encoder, purpose-built for autonomous agentic tasks on consumer hardware. Muse Glimmer…

cs.CV2026

MemoBench: Benchmarking World Modeling in Dynamically Changing Environments

Haoyu Chen, Kaichen Zhou, Hang Hua +11

Video generation models aspire to simulate dynamic environments, and several benchmarks now evaluate memory consistency across frames. However, most assess consistency only while t…

cs.CV2026

AC3S: Adaptive Conditioning for 3D-Aware Synthetic Data Generation

Eric Ji, Qiran Hu, Wufei Ma +4

Synthetic data generation has emerged as a powerful tool for improving data scalability in computer vision. Recent diffusion-based pipelines have demonstrated strong photorealism.…

cs.CV2026

SEMAGIC: Learning Semantically Consistent Deformable 3D Representations from In-the-Wild Images

Sky Cen, Wufei Ma, Guofeng Zhang +2

Learning deformable 3D object models from single-view in-the-wild images has enabled impressive 3D shape reconstruction without supervision. However, it remains unclear whether the…

cs.CV2026

LychSim: A Controllable and Interactive Simulation Framework for Vision Research

Wufei Ma, Chloe Wang, Siyi Chen +3

While self-supervised pretraining has reduced vision systems' reliance on synthetic data, simulation remains an indispensable tool for closed-loop optimization and rigorous out-of-…

cs.CV2026

PASR: Pose-Aware 3D Shape Retrieval from Occluded Single Views

Jiaxin Shi, Guofeng Zhang, Wufei Ma +3

Single-view 3D shape retrieval is a fundamental yet challenging task that is increasingly important with the growth of available 3D data. Existing approaches largely fall into two…

cs.CV2026

A Frame is Worth One Token: Efficient Generative World Modeling with Delta Tokens

Tommie Kerssies, Gabriele Berton, Ju He +5

Anticipating diverse future states is a central challenge in video world modeling. Discriminative world models produce a deterministic prediction that implicitly averages over poss…

cs.AI2025

Generative Adversarial Reasoner: Enhancing LLM Reasoning with Adversarial Reinforcement Learning

Qihao Liu, Luoxin Ye, Wufei Ma +2

Large language models (LLMs) with explicit reasoning capabilities excel at mathematical reasoning yet still commit process errors, such as incorrect calculations, brittle logic, an…

cs.CV2025

Perceptual Taxonomy: Evaluating and Guiding Hierarchical Scene Reasoning in Vision-Language Models

Jonathan Lee, Xingrui Wang, Jiawei Peng +9

We propose Perceptual Taxonomy, a structured process of scene understanding that first recognizes objects and their spatial configurations, then infers task-relevant properties suc…

cs.CV2025

TriDiff-4D: Fast 4D Generation through Diffusion-based Triplane Re-posing

Eddie Pokming Sheung, Qihao Liu, Wufei Ma +3

With the increasing demand for 3D animation, generating high-fidelity, controllable 4D avatars from textual descriptions remains a significant challenge. Despite notable efforts in…

cs.CV2025

Pursuing Minimal Sufficiency in Spatial Reasoning

Yejie Guo, Yunzhong Hou, Wufei Ma +2

Spatial reasoning, the ability to ground language in 3D understanding, remains a persistent challenge for Vision-Language Models (VLMs). We identify two fundamental bottlenecks: in…

cs.CV2025

4D-Animal: Freely Reconstructing Animatable 3D Animals from Videos

Shanshan Zhong, Jiawei Peng, Zehan Zheng +6

Existing methods for reconstructing animatable 3D animals from videos typically rely on sparse semantic keypoints to fit parametric models. However, obtaining such keypoints is lab…

cs.CV2025

SpatialLLM: A Compound 3D-Informed Design towards Spatially-Intelligent Large Multimodal Models

Wufei Ma, Luoxin Ye, Celso M de Melo +2

Humans naturally understand 3D spatial relationships, enabling complex reasoning like predicting collisions of vehicles from different directions. Current large multimodal models (…

cs.CV2025

SpatialReasoner: Towards Explicit and Generalizable 3D Spatial Reasoning

Wufei Ma, Yu-Cheng Chou, Qihao Liu +4

Despite recent advances on multi-modal models, 3D spatial reasoning remains a challenging task for state-of-the-art open-source and proprietary models. Recent studies explore data-…

cs.CV2025

DINeMo: Learning Neural Mesh Models with no 3D Annotations

Weijie Guo, Guofeng Zhang, Wufei Ma +1

Category-level 3D/6D pose estimation is a crucial step towards comprehensive 3D scene understanding, which would enable a broad range of applications in robotics and embodied AI. R…

cs.CV2025

Spatial457: A Diagnostic Benchmark for 6D Spatial Reasoning of Large Multimodal Models

Xingrui Wang, Wufei Ma, Tiezheng Zhang +3

Although large multimodal models (LMMs) have demonstrated remarkable capabilities in visual scene interpretation and reasoning, their capacity for complex and precise 3-dimensional…

cs.CV2024

3DSRBench: A Comprehensive 3D Spatial Reasoning Benchmark

Wufei Ma, Haoyu Chen, Guofeng Zhang +4

3D spatial reasoning is the ability to analyze and interpret the positions, orientations, and spatial relationships of objects within the 3D space. This allows models to develop a…

cs.CV2024

Rethinking Video-Text Understanding: Retrieval from Counterfactually Augmented Data

Wufei Ma, Kai Li, Zhongshi Jiang +5

Recent video-text foundation models have demonstrated strong performance on a wide variety of downstream video understanding tasks. Can these video-text models genuinely understand…

cs.CV2024★ 1 cited

ImageNet3D: Towards General-Purpose Object-Level 3D Understanding

Wufei Ma, Guanning Zeng, Guofeng Zhang +5

A vision model with general-purpose object-level 3D understanding should be capable of inferring both 2D (e.g., class name and bounding box) and 3D information (e.g., 3D location a…

cs.CV2024

Compositional 4D Dynamic Scenes Understanding with Physics Priors for Video Question Answering

Xingrui Wang, Wufei Ma, Angtian Wang +3

For vision-language models (VLMs), understanding the dynamic properties of objects and their interactions in 3D scenes from videos is crucial for effective reasoning about high-lev…

cs.CV2024

Uncertainty-Aware Deep Video Compression with Ensembles

Wufei Ma, Jiahao Li, Bin Li +1

Deep learning-based video compression is a challenging task, and many previous state-of-the-art learning-based video codecs use optical flows to exploit the temporal correlation be…

cs.CV2023

3D-Aware Visual Question Answering about Parts, Poses and Occlusions

Xingrui Wang, Wufei Ma, Zhuowan Li +2

Despite rapid progress in Visual question answering (VQA), existing datasets and models mainly focus on testing reasoning in 2D. However, it is important that VQA models also under…

cs.CV2023★ 2 cited

Animal3D: A Comprehensive Dataset of 3D Animal Pose and Shape

Jiacong Xu, Yi Zhang, Jiawei Peng +17

Accurately estimating the 3D pose and shape is an essential step towards understanding animal behavior, and can potentially benefit many downstream applications, such as wildlife c…

cs.CV2023★ 1 cited

Generating Images with 3D Annotations Using Diffusion Models

Wufei Ma, Qihao Liu, Jiahao Wang +11

Diffusion models have emerged as a powerful generative method, capable of producing stunning photo-realistic images from natural language descriptions. However, these models lack e…