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Justin Theiss

4 accepted papers

2026

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

CVPR 2026

The rapid advancement of Large Multimodal Models (LMMs) for 2D images and videos has sparked interest in extending these models to 3D scenes, with the goal of human-like visual-spatial intelligence. However, achieving deep spatial understanding comparable to human capabilities remains challenging fo

Cited by 0SourcecodeScholar
2025

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

NeurIPS 2025poster

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 interaction and enables embodied agents to perceive and act within real environments with human‑like capabilities. Howev…

Cited by 0SourceScholar
2025

InteractAvatar: Modeling Hand-Face Interaction in Photorealistic Avatars with Deformable Gaussians

ICCV 2025poster

With the rising interest from the community in digital avatars coupled with the importance of expressions and gestures in communication, modeling natural avatar behavior remains an important challenge across many industries such as teleconferencing, gaming, and AR/VR. Human hands are the primary too…

Cited by 0SourcePDFScholar
2022

Unpaired Image Translation via Vector Symbolic Architectures

ECCV 2022poster

"Image-to-image translation has played an important role in enabling synthetic data for computer vision. However, if the source and target domains have a large semantic mismatch, existing techniques often suffer from source content corruption aka semantic flipping. To address this problem, we propos…