Nikola Popovic

Affiliations:
  • INSAIT, Sofia, Bulgaria
  • ETH Zurich, Switzerland (PhD 2024)


According to our database1, Nikola Popovic authored at least 16 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2025
SceneSplat++: A Large Dataset and Comprehensive Benchmark for Language Gaussian Splatting.
CoRR, June, 2025

SceneSplat: Gaussian Splatting-based Scene Understanding with Vision-Language Pretraining.
CoRR, March, 2025

Leveraging Driver Field-of-View for Multimodal Ego-Trajectory Prediction.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
Rethinking Global Context in Crowd Counting.
Mach. Intell. Res., August, 2024

Dense, Sparse, and Weak Labels for Visual Understanding and Generation.
PhD thesis, 2024

2023
G-MEMP: Gaze-Enhanced Multimodal Ego-Motion Prediction in Driving.
CoRR, 2023

Spatially Multi-conditional Image Generation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Model-aware 3D Eye Gaze from Weak and Few-shot Supervisions.
Proceedings of the IEEE International Symposium on Mixed and Augmented Reality Adjunct, 2023

Token-Consistent Dropout For Calibrated Vision Transformers.
Proceedings of the IEEE International Conference on Image Processing, 2023

Surface Normal Clustering for Implicit Representation of Manhattan Scenes.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Neural Radiance Fields for Manhattan Scenes with Unknown Manhattan Frame.
CoRR, 2022

Gradient Obfuscation Checklist Test Gives a False Sense of Security.
CoRR, 2022

2021
Stochastic Layers in Vision Transformers.
CoRR, 2021

Boosting Crowd Counting with Transformers.
CoRR, 2021

Task Switching Network for Multi-task Learning.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

CompositeTasking: Understanding Images by Spatial Composition of Tasks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021


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