3 citations · 5 across the 7 of their papers we have counts for
8 papers
Geometric Reciprocity: Unlocking Self-Supervision for Stereoscopic Video Generation
Jingyi Lu, Kai Han
Monocular-to-stereo conversion synthesizes stereoscopic content from 2D videos for immersive 3D experiences. In modern Depth-Image-Based Rendering (DIBR) approaches, stereo inpaint…
Semantic-Enriched Latent Visual Reasoning
Tianrun Xu, Yue Sun, Qixun Wang +8
Multimodal latent-space reasoning aims to replace explicit thinking with images by performing visual reasoning directly in a compact latent space. However, existing approaches larg…
VAGS: Velocity Adaptive Guidance Scale for Image Editing and Generation
Yan Luo, Ahmadou Aidara, Jingyi Lu +3
Classifier-free guidance (CFG) is the primary control over how strongly text semantics move a flow-based sampler, yet standard practice holds its scale fixed across the entire ODE…
Inpaint4Drag: Repurposing Inpainting Models for Drag-Based Image Editing via Bidirectional Warping
Jingyi Lu, Kai Han
Drag-based image editing has emerged as a powerful paradigm for intuitive image manipulation. However, existing approaches predominantly rely on manipulating the latent space of ge…
Semantic Correspondence: Unified Benchmarking and a Strong Baseline
Kaiyan Zhang, Xinghui Li, Jingyi Lu +1
Establishing semantic correspondence is a challenging task in computer vision, aiming to match keypoints with the same semantic information across different images. Benefiting from…
ZeroBench: An Impossible Visual Benchmark for Contemporary Large Multimodal Models
Jonathan Roberts, Mohammad Reza Taesiri, Ansh Sharma +31
Large Multimodal Models (LMMs) exhibit shortfalls when interpreting images and, by some measures, have poorer spatial cognition than young children or animals. Despite this, they a…
RegionDrag: Fast Region-Based Image Editing with Diffusion Models
Jingyi Lu, Xinghui Li, Kai Han
Point-drag-based image editing methods, like DragDiffusion, have attracted significant attention. However, point-drag-based approaches suffer from computational overhead and misint…
SD4Match: Learning to Prompt Stable Diffusion Model for Semantic Matching
Xinghui Li, Jingyi Lu, Kai Han +1
In this paper, we address the challenge of matching semantically similar keypoints across image pairs. Existing research indicates that the intermediate output of the UNet within t…