2 citations · 2 across the 5 of their papers we have counts for
6 papers
Scaling Discovery Requires Forgetting
Shangyin Tan, Ben Zhou, Lakshya A Agrawal +8
Automated research with LLM agents has shown promising results in various domains. Through iterative refinement and scored verifiers, LLM agents are capable of discovering new idea…
InfiniSplat: Implicit Gaussian Decoding for Large-Baseline Monocular View Synthesis
Jiawei Wang, Hao Yu, Yongzhen Hu +7
Single-image feed-forward 3D Gaussian Splatting (3DGS) aims to directly generate a renderable 3D scene representation from one input image, avoiding the cost of multi-view capture…
InfiniDepth: Arbitrary-Resolution and Fine-Grained Depth Estimation with Neural Implicit Fields
Hao Yu, Haotong Lin, Jiawei Wang +7
Existing depth estimation methods are fundamentally limited to predicting depth on discrete image grids. Such representations restrict their scalability to arbitrary output resolut…
InstructUDrag: Joint Text Instructions and Object Dragging for Interactive Image Editing
Haoran Yu, Yi Shi
Text-to-image diffusion models have shown great potential for image editing, with techniques such as text-based and object-dragging methods emerging as key approaches. However, eac…
MatchAnything: Universal Cross-Modality Image Matching with Large-Scale Pre-Training
Xingyi He, Hao Yu, Sida Peng +4
Image matching, which aims to identify corresponding pixel locations between images, is crucial in a wide range of scientific disciplines, aiding in image registration, fusion, and…
MatchU: Matching Unseen Objects for 6D Pose Estimation from RGB-D Images
Junwen Huang, Hao Yu, Kuan-Ting Yu +3
Recent learning methods for object pose estimation require resource-intensive training for each individual object instance or category, hampering their scalability in real applicat…