2 citations · 3 across the 15 of their papers we have counts for
11 papers · 1 filter
One Editor, Many Edits: A Unified Training-Free Framework for Diverse Video Editing
Adheesh Sunil Juvekar, Onkar Kishor Susladkar, Kiet A. Nguyen +6
Video editing spans diverse editing paradigms, yet achieving high-quality instruction-guided and subject-guided editing within a single unified framework remains challenging. We in…
GraphVid: Interactive Graph-Controllable Video Generation
Vedant Shah, Onkar Susladkar, Tushar Prakash +5
Controllable video generation remains challenging due to the difficulty of specifying precise multi-object interactions using text prompts or motion-control inputs that primarily c…
ChronoVision: Temporal Reasoning via Latent State Reconstruction
Yifan Shen, Jian Xu, Boyi Li +6
Multimodal large language models excel at passive perception but struggle with complex visual cognitive tasks requiring multi-step temporal reasoning. This degradation largely stem…
ELSA3D: Elastic Semantic Anchoring for Unified 3D Understanding and Generation
Tianjiao Yu, Xinzhuo Li, Yifan Shen +4
Unified 3D foundation models aspire to generate 3D assets and reason about them in language within a single backbone, but their text-3D interaction remains largely implicit. Existi…
Phantom: Physics-Infused Video Generation via Joint Modeling of Visual and Latent Physical Dynamics
Ying Shen, Jerry Xiong, Tianjiao Yu +1
Recent advances in generative video modeling, driven by large-scale datasets and powerful architectures, have yielded remarkable visual realism. However, emerging evidence suggests…
EgoForge: Goal-Directed Egocentric World Simulator
Yifan Shen, Jiateng Liu, Xinzhuo Li +9
Generative world models have shown promise for simulating dynamic environments, yet egocentric video remains challenging due to rapid viewpoint changes, frequent hand-object intera…
DreamPartGen: Semantically Grounded Part-Level 3D Generation via Collaborative Latent Denoising
Tianjiao Yu, Xinzhuo Li, Muntasir Wahed +4
Understanding and generating 3D objects as compositions of meaningful parts is fundamental to human perception and reasoning. However, most text-to-3D methods overlook the semantic…
CoRe3D: Collaborative Reasoning as a Foundation for 3D Intelligence
Tianjiao Yu, Xinzhuo Li, Yifan Shen +2
Recent advances in large multimodal models suggest that explicit reasoning mechanisms play a critical role in improving model reliability, interpretability, and cross-modal alignme…
PartGS: Part-aware Modeling of Articulated Objects using 3D Gaussian Splatting
Tianjiao Yu, Vedant Shah, Muntasir Wahed +3
Articulated objects are common in the real world, yet modeling their structure and motion remains a challenging task for 3D reconstruction methods. In this work, we introduce Part$…
CALICO: Part-Focused Semantic Co-Segmentation with Large Vision-Language Models
Kiet A. Nguyen, Adheesh Juvekar, Tianjiao Yu +2
Recent advances in Large Vision-Language Models (LVLMs) have enabled general-purpose vision tasks through visual instruction tuning. While existing LVLMs can generate segmentation…
PRIMA: Multi-Image Vision-Language Models for Reasoning Segmentation
Muntasir Wahed, Kiet A. Nguyen, Adheesh Sunil Juvekar +6
Despite significant advancements in Large Vision-Language Models (LVLMs)' capabilities, existing pixel-grounding models operate in single-image settings, limiting their ability to…