PPaperPicks

Muzammal Naseer

26 papers at tracked venues · 16 at CORE A* · active 20242025

Venues

Frequent coauthors

Papers

  1. DyCON: Dynamic Uncertainty-aware Consistency and Contrastive Learning for Semi-supervised Medical Image Segmentation
  2. Enhancing Novel Object Detection via Cooperative Foundational Models
  3. Hierarchical Self-supervised Adversarial Training for Robust Vision Models in Histopathology
  4. How Good is my Video-LMM? Complex Video Reasoning and Robustness Evaluation Suite for Video-LMMs
  5. Learning to Prompt with Text Only Supervision for Vision-Language Models
  6. MixANT: Observation-Dependent Memory Propagation for Stochastic Dense Action Anticipation
  7. STEREO: A Two-Stage Framework for Adversarially Robust Concept Erasing from Text-to-Image Diffusion Models
  8. STING-BEE: Towards Vision-Language Model for Real-World X-ray Baggage Security Inspection
  9. Towards Evaluating the Robustness of Visual State Space Models
  10. VANE-Bench: Video Anomaly Evaluation Benchmark for Conversational LMMs
  11. Video-Panda: Parameter-efficient Alignment for Encoder-free Video-Language Models
  12. Vision-Language Neural Graph Featurization for Extracting Retinal Lesions
  13. BAPLe: Backdoor Attacks on Medical Foundational Models Using Prompt Learning
  14. Composed Video Retrieval via Enriched Context and Discriminative Embeddings
  15. Cross-Modal Self-Training: Aligning Images and Pointclouds to learn Classification without Labels
  16. GeoChat: Grounded Large Vision-Language Model for Remote Sensing
  17. Hierarchical Text-to-Vision Self Supervised Alignment for Improved Histopathology Representation Learning
  18. LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts
  19. Makeup-Guided Facial Privacy Protection via Untrained Neural Network Priors
  20. MedContext: Learning Contextual Cues for Efficient Volumetric Medical Segmentation
  21. On Evaluating Adversarial Robustness of Volumetric Medical Segmentation Models
  22. Probing the Efficacy of Federated Parameter-Efficient Fine-Tuning of Vision Transformers for Medical Image Classification
  23. PromptSmooth: Certifying Robustness of Medical Vision-Language Models via Prompt Learning
  24. Rethinking Transformers Pre-training for Multi-Spectral Satellite Imagery
  25. S3A: Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment
  26. VideoGrounding-DINO: Towards Open-Vocabulary Spatio- Temporal Video Grounding