11 papers
ABACUS: Adapting Unified Foundation Model for Bridging Image Count Understanding and Generation
Anindya Mondal, Sauradip Nag, Anjan Dutta
ABACUS is a unified vision-language model that handles object counting, crowd counting, referring-expression counting, and count-faithful image generation without any benchmark-spe…
Advances in 4D Representation: Geometry, Motion, and Interaction
Mingrui Zhao, Sauradip Nag, Kai Wang +5
We present a survey on 4D generation and reconstruction, a fast-evolving subfield of computer graphics whose developments have been propelled by recent advances in neural fields, g…
Articulate That Object Part (ATOP): 3D Part Articulation via Text and Motion Personalization
Aditya Vora, Sauradip Nag, Kai Wang +1
We present ATOP (Articulate That Object Part), a novel few-shot method based on motion personalization to articulate a static 3D object with respect to a part and its motion as pre…
Functionalization via Structure Completion and Motion Rectification
Mingrui Zhao, Sai Raj Kishore Perla, Kai Wang +8
Acquisition and creation of 3D assets have been largely view- or appearance-driven. As a result, existing digital 3D models often lack the requisite structural components to functi…
CountLoop: Training-Free High-Instance Image Generation via Iterative Agent Guidance
Anindya Mondal, Ayan Banerjee, Sauradip Nag +3
Diffusion models excel at photorealistic synthesis but struggle with precise object counts, especially in high-density settings. We introduce COUNTLOOP, a training-free framework t…
RespoDiff: Dual-Module Bottleneck Transformation for Responsible & Faithful T2I Generation
Silpa Vadakkeeveetil Sreelatha, Sauradip Nag, Muhammad Awais +2
The rapid advancement of diffusion models has enabled high-fidelity and semantically rich text-to-image generation; however, ensuring fairness and safety remains an open challenge.…