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Found 11 papers, 4 papers with code
No More Ambiguity in 360° Room Layout via Bi-Layout Estimation
A unique property of our Bi-Layout model is its ability to inherently detect ambiguous regions by comparing the two predictions.
PoCo: Point Context Cluster for RGBD Indoor Place Recognition
We present a novel end-to-end algorithm (PoCo) for the indoor RGB-D place recognition task, aimed at identifying the most likely match for a given query frame within a reference database.
GDA: Generalized Diffusion for Robust Test-time Adaptation
For vision tasks, recent studies have shown that test-time adaptation employing diffusion models can achieve state-of-the-art accuracy improvements on OOD samples by generating new samples that align with the model's domain without the need to modify the model's weights.
Tabletop Transparent Scene Reconstruction via Epipolar-Guided Optical Flow with Monocular Depth Completion Prior
Reconstructing transparent objects using affordable RGB-D cameras is a persistent challenge in robotic perception due to inconsistent appearances across views in the RGB domain and inaccurate depth readings in each single-view.
ImGeoNet: Image-induced Geometry-aware Voxel Representation for Multi-view 3D Object Detection
The results demonstrate that ImGeoNet outperforms the current state-of-the-art multi-view image-based method, ImVoxelNet, on all three datasets in terms of detection accuracy.
Ranked #24 on
3D Object Detection
on ScanNetV2
ReCLIP: Refine Contrastive Language Image Pre-Training with Source Free Domain Adaptation
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 without seeing any example, which leads to potential benefits to many tasks that have no labeled data.
Bidirectional Alignment for Domain Adaptive Detection with Transformers
We propose a Bidirectional Alignment for domain adaptive Detection with Transformers (BiADT) to improve cross domain object detection performance.
SupeRGB-D: Zero-shot Instance Segmentation in Cluttered Indoor Environments
We introduce a zero-shot split for Tabletop Objects Dataset (TOD-Z) to enable this study and present a method that uses annotated objects to learn the ``objectness'' of pixels and generalize to unseen object categories in cluttered indoor environments.
Learning Feature Decomposition for Domain Adaptive Monocular Depth Estimation
In this paper, we propose a novel UDA method for MDE, referred to as Learning Feature Decomposition for Adaptation (LFDA), which learns to decompose the feature space into content and style components.
Acted vs. Improvised: Domain Adaptation for Elicitation Approaches in Audio-Visual Emotion Recognition
Key challenges in developing generalized automatic emotion recognition systems include scarcity of labeled data and lack of gold-standard references.
MEBOW: Monocular Estimation of Body Orientation In the Wild
We present COCO-MEBOW (Monocular Estimation of Body Orientation in the Wild), a new large-scale dataset for orientation estimation from a single in-the-wild image.
