3 citations · 4 across the 8 of their papers we have counts for
9 papers
Revisiting Model Stitching In the Foundation Model Era
Zheda Mai, Ke Zhang, Fu-En Wang +6
Model stitching, connecting early layers of one model (source) to later layers of another (target) via a light stitch layer, has served as a probe of representational compatibility…
OpenM3D: Open Vocabulary Multi-view Indoor 3D Object Detection without Human Annotations
Peng-Hao Hsu, Ke Zhang, Fu-En Wang +6
Open-vocabulary (OV) 3D object detection is an emerging field, yet its exploration through image-based methods remains limited compared to 3D point cloud-based methods. We introduc…
Details Matter for Indoor Open-vocabulary 3D Instance Segmentation
Sanghun Jung, Jingjing Zheng, Ke Zhang +10
Unlike closed-vocabulary 3D instance segmentation that is often trained end-to-end, open-vocabulary 3D instance segmentation (OV-3DIS) often leverages vision-language models (VLMs)…
Advancing Multimodal LLMs by Large-Scale 3D Visual Instruction Dataset Generation
Liu He, Xiao Zeng, Yizhi Song +7
Multimodal Large Language Models (MLLMs) struggle with accurately capturing camera-object relations, especially for object orientation, camera viewpoint, and camera shots. This ste…
GenRC: Generative 3D Room Completion from Sparse Image Collections
Ming-Feng Li, Yueh-Feng Ku, Hong-Xuan Yen +5
Sparse RGBD scene completion is a challenging task especially when considering consistent textures and geometries throughout the entire scene. Different from existing solutions tha…
BaFTA: Backprop-Free Test-Time Adaptation For Zero-Shot Vision-Language Models
Xuefeng Hu, Ke Zhang, Min Sun +3
Large-scale pretrained vision-language models like CLIP have demonstrated remarkable zero-shot image classification capabilities across diverse domains. To enhance CLIP's performan…
No More Ambiguity in 360° Room Layout via Bi-Layout Estimation
Yu-Ju Tsai, Jin-Cheng Jhang, Jingjing Zheng +5
Inherent ambiguity in layout annotations poses significant challenges to developing accurate 360° room layout estimation models. To address this issue, we propose a novel Bi-Layout…
GDA: Generalized Diffusion for Robust Test-time Adaptation
Yun-Yun Tsai, Fu-Chen Chen, Albert Y. C. Chen +4
Machine learning models struggle with generalization when encountering out-of-distribution (OOD) samples with unexpected distribution shifts. For vision tasks, recent studies have…
ReCLIP: Refine Contrastive Language Image Pre-Training with Source Free Domain Adaptation
Xuefeng Hu, Ke Zhang, Lu Xia +9
Large-scale Pre-Training Vision-Language Model such as CLIP has demonstrated outstanding performance in zero-shot classification, e.g. achieving 76.3% top-1 accuracy on ImageNet wi…