7 citations · 8 across the 10 of their papers we have counts for
17 papers
OverLay++: Dense-Overlap Layout-to-Image Generation Dataset
Shivansh Aggarwal, Shresth Grover, Divyansh Srivastava +7
Layout-to-Image generation has made substantial progress in spatial and object-level control. However, existing methods still struggle with complex scenes containing many overlappi…
NaLA: A 3D Native LLM Layout Agent for High-quality 3D Scene Generation
Cheng Wan, Yongsen Mao, Wenzheng Wu +7
Recently, Large Language Models (LLMs) have emerged as promising layout agents for 3D scene generation. Existing layout agents still suffer from implausible layout generation becau…
CyCLeGen: Cycle-Consistent Layout Prediction and Image Generation in Vision Foundation Models
Xiaojun Shan, Haoyu Shen, Yucheng Mao +5
We present CyCLeGen, a unified vision-language foundation model capable of both image understanding and image generation within a single autoregressive framework. Unlike existing v…
PixARMesh: Autoregressive Mesh-Native Single-View Scene Reconstruction
Xiang Zhang, Sohyun Yoo, Hongrui Wu +3
We introduce PixARMesh, a method to autoregressively reconstruct complete 3D indoor scene meshes directly from a single RGB image. Unlike prior methods that rely on implicit signed…
CVP: Central-Peripheral Vision-Inspired Multimodal Model for Spatial Reasoning
Zeyuan Chen, Xiang Zhang, Haiyang Xu +2
We present a central-peripheral vision-inspired framework (CVP), a simple yet effective multimodal model for spatial reasoning that draws inspiration from the two types of human vi…
Gaussian Swaying: Surface-Based Framework for Aerodynamic Simulation with 3D Gaussians
Hongru Yan, Xiang Zhang, Zeyuan Chen +2
Branches swaying in the breeze, flags rippling in the wind, and boats rocking on the water all show how aerodynamics shape natural motion -- an effect crucial for realism in vision…
C3Editor: Achieving Controllable Consistency in 2D Model for 3D Editing
Zeng Tao, Zheng Ding, Zeyuan Chen +3
Existing 2D-lifting-based 3D editing methods often encounter challenges related to inconsistency, stemming from the lack of view-consistent 2D editing models and the difficulty of…
OverLayBench: A Benchmark for Layout-to-Image Generation with Dense Overlaps
Bingnan Li, Chen-Yu Wang, Haiyang Xu +7
Despite steady progress in layout-to-image generation, current methods still struggle with layouts containing significant overlap between bounding boxes. We identify two primary ch…
Exploring the Equivalence of Closed-Set Generative and Real Data Augmentation in Image Classification
Haowen Wang, Guowei Zhang, Xiang Zhang +4
In this paper, we address a key scientific problem in machine learning: Given a training set for an image classification task, can we train a generative model on this dataset to en…
VertexRegen: Mesh Generation with Continuous Level of Detail
Xiang Zhang, Yawar Siddiqui, Armen Avetisyan +3
We introduce VertexRegen, a novel mesh generation framework that enables generation at a continuous level of detail. Existing autoregressive methods generate meshes in a partial-to…
YOLO-Count: Differentiable Object Counting for Text-to-Image Generation
Guanning Zeng, Xiang Zhang, Zirui Wang +4
We propose YOLO-Count, a differentiable open-vocabulary object counting model that tackles both general counting challenges and enables precise quantity control for text-to-image (…
DepR: Depth Guided Single-view Scene Reconstruction with Instance-level Diffusion
Qingcheng Zhao, Xiang Zhang, Haiyang Xu +4
We propose DepR, a depth-guided single-view scene reconstruction framework that integrates instance-level diffusion within a compositional paradigm. Instead of reconstructing the e…
Lay-Your-Scene: Natural Scene Layout Generation with Diffusion Transformers
Divyansh Srivastava, Xiang Zhang, He Wen +2
We present Lay-Your-Scene (shorthand LayouSyn), a novel text-to-layout generation pipeline for natural scenes. Prior scene layout generation methods are either closed-vocabulary or…
OmniControlNet: Dual-stage Integration for Conditional Image Generation
Yilin Wang, Haiyang Xu, Xiang Zhang +4
We provide a two-way integration for the widely adopted ControlNet by integrating external condition generation algorithms into a single dense prediction method and incorporating i…
Bayesian Diffusion Models for 3D Shape Reconstruction
Haiyang Xu, Yu Lei, Zeyuan Chen +4
We present Bayesian Diffusion Models (BDM), a prediction algorithm that performs effective Bayesian inference by tightly coupling the top-down (prior) information with the bottom-u…
Text Spotting Transformers
Xiang Zhang, Yongwen Su, Subarna Tripathi +1
In this paper, we present TExt Spotting TRansformers (TESTR), a generic end-to-end text spotting framework using Transformers for text detection and recognition in the wild. TESTR…
Pose Recognition with Cascade Transformers
Ke Li, Shijie Wang, Xiang Zhang +3
In this paper, we present a regression-based pose recognition method using cascade Transformers. One way to categorize the existing approaches in this domain is to separate them in…