5 papers
Robust Onion: Peeling Open Vocab Object Detectors Under Noise
Priyank Pathak, Mukilan Karuppasamy, Aaditya Baranwal +2
The impact of real-world noise on Open Vocabulary Object Detectors (OV-ODs) remains poorly understood due to their architectural complexity. We present our comprehensive analysis R…
CoSPlan: Corrective Sequential Planning via Scene Graph Incremental Updates
Shresth Grover, Priyank Pathak, Akash Kumar +1
Vision Language Models (VLMs) have shown promising planning capabilities, yet their success remains confined to the text domain, leaving visual decision-making relatively underexpl…
Coarse Attribute Prediction with Task Agnostic Distillation for Real World Clothes Changing ReID
Priyank Pathak, Yogesh S Rawat
This work focuses on Clothes Changing Re-IDentification (CC-ReID) for the real world. Existing works perform well with high-quality (HQ) images, but struggle with low-quality (LQ)…
Colors See Colors Ignore: Clothes Changing ReID with Color Disentanglement
Priyank Pathak, Yogesh S. Rawat
Clothes-Changing Re-Identification (CC-ReID) aims to recognize individuals across different locations and times, irrespective of clothing. Existing methods often rely on additional…
LR0.FM: Low-Res Benchmark and Improving Robustness for Zero-Shot Classification in Foundation Models
Priyank Pathak, Shyam Marjit, Shruti Vyas +1
Visual-language foundation Models (FMs) exhibit remarkable zero-shot generalization across diverse tasks, largely attributed to extensive pre-training on largescale datasets. Howev…