Lift3D: Synthesize 3D Training Data by Lifting 2D GAN to 3D Generative Radiance Field
Comments CVPR 2023
期刊&会议
CVPR
Conference on Computer Vision and Pattern Recognition · 会议 · Computer Vision
Devil's on the Edges: Selective Quad Attention for Scene Graph Generation
Comments Accepted at CVPR 2023; Project page at https://cvlab.postech.ac.kr/research/SQUAT/
Towards Unified Scene Text Spotting based on Sequence Generation
Comments Accepted to CVPR 2023
$R^{2}$Former: Unified $R$etrieval and $R$eranking Transformer for Place Recognition
Comments CVPR
RoSteALS: Robust Steganography using Autoencoder Latent Space
Comments accepted to CVPR WMF 2023
Exposing and Mitigating Spurious Correlations for Cross-Modal Retrieval
Comments CVPR'23 MULA Workshop
TopNet: Transformer-based Object Placement Network for Image Compositing
Comments CVPR
EGA-Depth: Efficient Guided Attention for Self-Supervised Multi-Camera Depth Estimation
Comments CVPR 2023 Workshop on Autonomous Driving
Vita-CLIP: Video and text adaptive CLIP via Multimodal Prompting
Comments Accepted at CVPR-2023. Codes/models available at https://github.com/TalalWasim/Vita-CLIP
Viewpoint Equivariance for Multi-View 3D Object Detection
Comments 11 pages, 4 figures; accepted to CVPR 2023
Egocentric Video Task Translation
Comments Accepted by CVPR 2023 (Highlight), Project website: https://vision.cs.utexas.edu/projects/egot2/
Dynamic Multimodal Fusion
Comments Accepted by 6th Multi-Modal Learning and Applications Workshop (MULA), CVPR 2023. Code available at: https://github.com/zihuixue/DynMM
PaCa-ViT: Learning Patch-to-Cluster Attention in Vision Transformers
Comments CVPR 2023
$\text{DC}^2$: Dual-Camera Defocus Control by Learning to Refocus
Comments CVPR 2023. See the project page at https://defocus-control.github.io
Visual Dependency Transformers: Dependency Tree Emerges from Reversed Attention
Comments CVPR 2023
Neural Fields meet Explicit Geometric Representation for Inverse Rendering of Urban Scenes
Comments CVPR 2023. Project page: https://nv-tlabs.github.io/fegr/
Instant-NVR: Instant Neural Volumetric Rendering for Human-object Interactions from Monocular RGBD Stream
Comments CVPR 2023
VLPD: Context-Aware Pedestrian Detection via Vision-Language Semantic Self-Supervision
Comments Accepted by CVPR 2023
Zero-shot Generative Model Adaptation via Image-specific Prompt Learning
Comments Accepted by CVPR 2023. GitHub: https://github.com/Picsart-AI-Research/IPL-Zero-Shot-Generative-Model-Adaptation
Continual Detection Transformer for Incremental Object Detection
Comments Accepted to CVPR 2023
Multi-view Adversarial Discriminator: Mine the Non-causal Factors for Object Detection in Unseen Domains
Comments CVPR 2023 (Highlight, top 2.5%). Pytorch vs. MindSpore Code at "https://github.com/K2OKOH/MAD"
Learning Instance-Level Representation for Large-Scale Multi-Modal Pretraining in E-commerce
Comments 16 pages, 10 figures, accepted by CVPR 2023
Uncurated Image-Text Datasets: Shedding Light on Demographic Bias
Comments CVPR 2023
MethaneMapper: Spectral Absorption aware Hyperspectral Transformer for Methane Detection
Comments 16 pages, 9 figures, 3 tables, Accepted to Computer Vision and Pattern Recognition (CVPR 2023) conference. CVPR 2023 Highlights paper
Exploring the Utility of Self-Supervised Pretraining Strategies for the Detection of Absent Lung Sliding in M-Mode Lung Ultrasound
Comments 10 pages, 6 figures, to be published in the 2023 Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops
MEnsA: Mix-up Ensemble Average for Unsupervised Multi Target Domain Adaptation on 3D Point Clouds
Comments Accepted at Workshop on Learning with Limited Labelled Data (CVPR 2023)
Long-Tailed Visual Recognition via Self-Heterogeneous Integration with Knowledge Excavation
Comments CVPR 2023
CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIP
Comments CVPR 2023
MagicNet: Semi-Supervised Multi-Organ Segmentation via Magic-Cube Partition and Recovery
Comments Accepted by CVPR 2023
Teaching Matters: Investigating the Role of Supervision in Vision Transformers
Comments Website: see https://www.cs.umd.edu/~sakshams/vit_analysis. Code: see https://www.github.com/mwalmer-umd/vit_analysis. The first two authors contributed equally. Accepted to CVPR 2023 as conference paper
