Ankit Jha

Orcid: 0000-0002-1063-8978

According to our database1, Ankit Jha authored at least 41 papers between 2020 and 2026.

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

Timeline

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Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
BioVLM: Routing Prompts, Not Parameters, for Cross-Modality Generalization in Biomedical VLMs.
CoRR, April, 2026

MMLGNet: Cross-Modal Alignment of Remote Sensing Data using CLIP.
CoRR, January, 2026

SDHSI-Net: Learning Better Representations for Hyperspectral Images via Self-Distillation.
CoRR, January, 2026

Reconstruction Guided Few-shot Network For Remote Sensing Image Classification.
CoRR, January, 2026

2025
Two-Stage Vision Transformer for Image Restoration: Colorization Pretraining + Residual Upsampling.
CoRR, December, 2025

FedMVP: Federated Multi-modal Visual Prompt Tuning for Vision-Language Models.
CoRR, April, 2025

Towards molecular structure discovery from cryo-ET density volumes via modelling auxiliary semantic prototypes.
Briefings Bioinform., January, 2025

Meta-Learning to Teach Semantic Prompts for Open Domain Generalization in Vision-Language Models.
Trans. Mach. Learn. Res., 2025

RS3Lip: Consistency for remote sensing image classification on part embeddings using self-supervised learning and CLIP.
Comput. Vis. Image Underst., 2025

Foundation Models and Adaptive Feature Selection: A Synergistic Approach to Video Question Answering.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2025

A new set of metrics for measuring the complexity of OCL expressions.
Proceedings of the Joint Proceedings of the STAF 2025 Workshops: OCL, 2025

FedMVP: Federated Multimodal Visual Prompt Tuning for Vision-Language Models.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

OSLoPrompt: Bridging Low-Supervision Challenges and Open-Set Domain Generalization in CLIP.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024
In the Era of Prompt Learning with Vision-Language Models.
CoRR, 2024

Blockchain based Decentralized Petition System.
CoRR, 2024

StyLIP: Multi-Scale Style-Conditioned Prompt Learning for CLIP-based Domain Generalization.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Learning Class and Domain Augmentations for Single-Source Open-Domain Generalization.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Verifying UML Models Annotated with OCL Strings.
Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems, 2024

GraphVL: Graph-Enhanced Semantic Modeling via Vision-Language Models for Generalized Class Discovery✱.
Proceedings of the Fifteenth Indian Conference on Computer Vision Graphics and Image Processing, 2024

Can Commonsense Knowledge Improve CLIP's Performance in Cross-Domain VQA?✱.
Proceedings of the Fifteenth Indian Conference on Computer Vision Graphics and Image Processing, 2024

Elevating All Zero-Shot Sketch-Based Image Retrieval Through Multimodal Prompt Learning.
Proceedings of the Computer Vision - ECCV 2024, 2024

Unknown Prompt, the only Lacuna: Unveiling CLIP's Potential for Open Domain Generalization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

CDAD-Net: Bridging Domain Gaps in Generalized Category Discovery.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

COSMo: CLIP Talks on Open-Set Multi-Target Domain Adaptation.
Proceedings of the 35th British Machine Vision Conference, 2024

2023
MAML-SR: Self-adaptive super-resolution networks via multi-scale optimized attention-aware meta-learning.
Pattern Recognit. Lett., September, 2023

Beyond Boundaries: A Novel Data-Augmentation Discourse for Open Domain Generalization.
Trans. Mach. Learn. Res., 2023

MDFS-Net: Multidomain Few Shot Classification for Hyperspectral Images With Support Set Reconstruction.
IEEE Trans. Geosci. Remote. Sens., 2023

GAF-Net: Improving the Performance of Remote Sensing Image Fusion using Novel Global Self and Cross Attention Learning.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

HAVE-Net: Hallucinated Audio-Visual Embeddings for Few-Shot Classification with Unimodal Cues.
Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023

C-SAW: Self-Supervised Prompt Learning for Image Generalization in Remote Sensing.
Proceedings of the Fourteenth Indian Conference on Computer Vision, 2023

Automatic Benchmark Generation for Object Constraint Language.
Proceedings of the IEEE Conference on Software Testing, Verification and Validation, 2023

AD-CLIP: Adapting Domains in Prompt Space Using CLIP.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

APPLeNet: Visual Attention Parameterized Prompt Learning for Few-Shot Remote Sensing Image Generalization using CLIP.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

GOPro: Generate and Optimize Prompts in CLIP using Self-Supervised Learning.
Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022
GesSure - A Robust Face-Authentication enabled Dynamic Gesture Recognition GUI Application.
CoRR, 2022

Next Generation Ultra-sensitive Surface Plasmon Resonance Biosensors.
Proceedings of the Machine Learning, Image Processing, Network Security and Data Sciences, 2022

2021
ADA-AT/DT: An Adversarial Approach for Cross-Domain and Cross-Task Knowledge Transfer.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

<i>S</i><sup>3</sup> DMT-Net: improving soft sharing based multi-task CNN using task-specific distillation and cross-task interactions.
Proceedings of the ICVGIP '21: Indian Conference on Computer Vision, Graphics and Image Processing, Jodhpur, India, December 19, 2021

2020
MT-UNET: A Novel U-Net Based Multi-Task Architecture For Visual Scene Understanding.
Proceedings of the IEEE International Conference on Image Processing, 2020

AdaMT-Net: An Adaptive Weight Learning Based Multi-Task Learning Model For Scene Understanding.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

SD-MTCNN: Self-Distilled Multi-Task CNN.
Proceedings of the 31st British Machine Vision Conference 2020, 2020


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