14.06.2024
MCML at CVPR 2024
The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024 (CVPR 2024). Seattle, Washington, United States, June 17-21, 2024
We are happy to announce that MCML researchers are represented with 37 papers at CVPR 2024:
S. Aneja, J. Thies, A. Dai and M. Nießner.
FaceTalk: Audio-Driven Motion Diffusion for Neural Parametric Head Models.
DOI.
FaceTalk: Audio-Driven Motion Diffusion for Neural Parametric Head Models.
DOI.
L. Bastian, Y. Xie, N. Navab and Z. Lähner.
Hybrid Functional Maps for Crease-Aware Non-Isometric Shape Matching.
DOI.
Hybrid Functional Maps for Crease-Aware Non-Isometric Shape Matching.
DOI.
M. Brahimi, B. Haefner, Z. Ye, B. Goldluecke and D. Cremers.
Sparse Views, Near Light: A Practical Paradigm for Uncalibrated Point-light Photometric Stereo.
DOI.
Sparse Views, Near Light: A Practical Paradigm for Uncalibrated Point-light Photometric Stereo.
DOI.
D. Cao, M. Eisenberger, N. E. Amrani, D. Cremers and F. Bernard.
Spectral Meets Spatial: Harmonising 3D Shape Matching and Interpolation.
DOI.
Spectral Meets Spatial: Harmonising 3D Shape Matching and Interpolation.
DOI.
Y. Chen, Y. Di, G. Zhai, F. Manhardt, C. Zhang, R. Zhang, F. Tombari, N. Navab and B. Busam.
SecondPose: SE(3)-Consistent Dual-Stream Feature Fusion for Category-Level Pose Estimation.
DOI.
SecondPose: SE(3)-Consistent Dual-Stream Feature Fusion for Category-Level Pose Estimation.
DOI.
D. Z. Chen, H. Li, H.-Y. Lee, S. Tulyakov and M. Nießner.
SceneTex: High-Quality Texture Synthesis for Indoor Scenes via Diffusion Priors.
DOI.
SceneTex: High-Quality Texture Synthesis for Indoor Scenes via Diffusion Priors.
DOI.
C. Diller, T. Funkhouser and A. Dai.
FutureHuman3D: Forecasting Complex Long-Term 3D Human Behavior from Video Observations.
DOI.
FutureHuman3D: Forecasting Complex Long-Term 3D Human Behavior from Video Observations.
DOI.
V. Ehm, M. Gao, P. Roetzer, M. Eisenberger, D. Cremers and F. Bernard.
Partial-to-Partial Shape Matching with Geometric Consistency.
DOI.
Partial-to-Partial Shape Matching with Geometric Consistency.
DOI.
M. Ghahremani, M. Khateri, B. Jian, B. Wiestler, E. Adeli and C. Wachinger.
H-ViT: A Hierarchical Vision Transformer for Deformable Image Registration.
DOI.
H-ViT: A Hierarchical Vision Transformer for Deformable Image Registration.
DOI.
S. Giebenhain, T. Kirschstein, M. Georgopoulos, M. Rünz, L. Agapito and M. Nießner.
MonoNPHM: Dynamic Head Reconstruction from Monocular Videos.
DOI.
MonoNPHM: Dynamic Head Reconstruction from Monocular Videos.
DOI.
K. Han, D. Muhle, F. Wimbauer and D. Cremers.
Boosting Self-Supervision for Single-View Scene Completion via Knowledge Distillation.
DOI.
Boosting Self-Supervision for Single-View Scene Completion via Knowledge Distillation.
DOI.
L. Höllein, A. Božič, N. Müller, D. Novotny, H.-Y. Tseng, C. Richardt, M. Zollhöfer and M. Nießner.
ViewDiff: 3D-Consistent Image Generation with Text-to-Image Models.
DOI.
ViewDiff: 3D-Consistent Image Generation with Text-to-Image Models.
DOI.
J. Huang, H. Yu, K.-T. Yu, N. Navab, S. Ilic and B. Busam.
MatchU: Matching Unseen Objects for 6D Pose Estimation from RGB-D Images.
DOI.
MatchU: Matching Unseen Objects for 6D Pose Estimation from RGB-D Images.
DOI.
H. Jung, G. Zhai, S.-C. Wu, P. Ruhkamp, H. Schieber, G. Rizzoli, P. Wang, H. Zhao, L. Garattoni, S. Meier, D. Roth, N. Navab and B. Busam.
HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarios.
DOI.
HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarios.
DOI.
T. Kirschstein, S. Giebenhain and M. Nießner.
DiffusionAvatars: Deferred Diffusion for High-fidelity 3D Head Avatars.
DOI.
DiffusionAvatars: Deferred Diffusion for High-fidelity 3D Head Avatars.
DOI.
P. Kocsis, J. Philip, K. Sunkavalli, M. Nießner and Y. Hold-Geoffroy.
LightIt: Illumination Modeling and Control for Diffusion Models.
DOI.
LightIt: Illumination Modeling and Control for Diffusion Models.
DOI.
P. Kocsis, V. Sitzmann and M. Nießner.
Intrinsic Image Diffusion for Indoor Single-view Material Estimation.
DOI.
Intrinsic Image Diffusion for Indoor Single-view Material Estimation.
DOI.
N. Müller, K. Schwarz, B. Rössle, L. Porzi, S. R. Bulò, M. Nießner and P. Kontschieder.
MultiDiff: Consistent Novel View Synthesis from a Single Image.
DOI.
MultiDiff: Consistent Novel View Synthesis from a Single Image.
DOI.
S. Niedermayr, J. Stumpfegger and R. Westermann.
Compressed 3D Gaussian Splatting for Accelerated Novel View Synthesis.
DOI.
Compressed 3D Gaussian Splatting for Accelerated Novel View Synthesis.
DOI.
S. Qian, T. Kirschstein, L. Schoneveld, D. Davoli, S. Giebenhain and M. Nießner.
GaussianAvatars: Photorealistic Head Avatars with Rigged 3D Gaussians.
DOI.
GaussianAvatars: Photorealistic Head Avatars with Rigged 3D Gaussians.
DOI.
C. Reich, B. Debnath, D. Patel, T. Prangemeier, D. Cremers and S. Chakradhar.
Deep Video Codec Control for Vision Models. (Workshop paper).
PDF.
Deep Video Codec Control for Vision Models. (Workshop paper).
PDF.
C. Reich, O. Hahn, D. Cremers, S. Roth and B. Debnath.
A Perspective on Deep Vision Performance with Standard Image and Video Codecs. (Workshop paper).
PDF.
A Perspective on Deep Vision Performance with Standard Image and Video Codecs. (Workshop paper).
PDF.
D. Rozenberszki, O. Litany and A. Dai.
UnScene3D: Unsupervised 3D Instance Segmentation for Indoor Scenes.
DOI.
UnScene3D: Unsupervised 3D Instance Segmentation for Indoor Scenes.
DOI.
Y. Siddiqui, A. Alliegro, A. Artemov, T. Tommasi, D. Sirigatti, V. Rosov, A. Dai and M. Nießner.
MeshGPT: Generating Triangle Meshes with Decoder-Only Transformers.
DOI.
MeshGPT: Generating Triangle Meshes with Decoder-Only Transformers.
DOI.
J. Tang, A. Dai, Y. Nie, L. Markhasin, J. Thies and M. Niessner.
DPHMs: Diffusion Parametric Head Models for Depth-based Tracking.
DOI.
DPHMs: Diffusion Parametric Head Models for Depth-based Tracking.
DOI.
J. Tang, Y. Nie, L. Markhasin, A. Dai, J. Thies and M. Nießner.
DiffuScene: Denoising Diffusion Models for Generative Indoor Scene Synthesis.
DOI.
DiffuScene: Denoising Diffusion Models for Generative Indoor Scene Synthesis.
DOI.
A. Toker, M. Eisenberger, D. Cremers and L. Leal-Taixé.
SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation.
DOI.
SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation.
DOI.
S. Weber, T. Dagès, M. Gao and D. Cremers.
Finsler-Laplace-Beltrami Operators with Application to Shape Analysis.
DOI.
Finsler-Laplace-Beltrami Operators with Application to Shape Analysis.
DOI.
S. Weber, B. Zöngür, N. Araslanov and D. Cremers.
Flattening the Parent Bias: Hierarchical Semantic Segmentation in the Poincaré Ball.
DOI.
Flattening the Parent Bias: Hierarchical Semantic Segmentation in the Poincaré Ball.
DOI.
F. Wimbauer, B. Wu, E. Schoenfeld, X. Dai, J. Hou, Z. He, A. Sanakoyeu, P. Zhang, S. Tsai, J. Kohler, C. Rupprecht, D. Cremers, P. Vajda and J. Wang.
Cache Me if You Can: Accelerating Diffusion Models through Block Caching.
DOI.
Cache Me if You Can: Accelerating Diffusion Models through Block Caching.
DOI.
H. Wu, X. Zuo, S. Leutenegger, O. Litany, K. Schindler and S. Huang.
Dynamic LiDAR Re-simulation using Compositional Neural Fields.
DOI.
Dynamic LiDAR Re-simulation using Compositional Neural Fields.
DOI.
L. Yang, L. Hoyer, M. Weber, T. Fischer, D. Dai, L. Leal-Taixé, D. Cremers, M. Pollefeys and L. Van Gool.
MICDrop: Masking Image and Depth Features via Complementary Dropout for Domain-Adaptive Semantic Segmentation. (Workshop paper).
URL.
MICDrop: Masking Image and Depth Features via Complementary Dropout for Domain-Adaptive Semantic Segmentation. (Workshop paper).
URL.
14.06.2024
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