Abhinav Shrivastava
Associate Professor
Researches computer vision and machine learning, including video understanding, self-supervised learning and neural representations.
Abhinav Shrivastava's lab at UMD works on video understanding and generative & foundation models. 70 papers since 2023, 48 at top venues, mostly CVPR and ECCV. 10 PhD students. 31 alumni, most often to Amazon and Meta.
At a glance
- papers, 2023–2026
- 18/ year
- at T1 venues
- 69%
- PhD students
- 10
- MS students
- 0
- alumni listed
- 31
Papers by yearfrom the lab homepage, 2023–2026
- 10 papers2026 · T1 7 · collecting
- 10 papers2025 · T1 6
- 32 papers2024 · T1 20
- 18 papers2023 · T1 15
T1 venuesOtherVenues: CVPR, ECCV, WACV, ICCV, ICLR
Research focuspaper titles that use each topic's words
- Video understanding15 papers
- Generative & foundation models8 papers
- neural representations2 papers
- self-supervised1 paper
- self-supervised learning0 papers
Paper list
From the lab homepage.
202610 papers
- CVPR (T1)Efficient and High-Fidelity Omni Modality Retrieval (opens in a new tab)
- ICLR (T1)Evolutionary Caching to Accelerate Your Off-the-Shelf Diffusion Model (opens in a new tab)
- MM Intelligence Workshop, ICLRGrowing Visual Generative Capacity for Pre-Trained MLLMs (opens in a new tab)
- WACVHow to Design and Train Your Implicit Neural Representation for Video Compression (opens in a new tab)
- ICLR (T1)NeRV-Diffusion: Diffuse Implicit Neural Representation for Video Synthesis (opens in a new tab)
- CVPR (T1)Scale Space Diffusion (opens in a new tab)
- BMVCTeCoNeRV: Leveraging Temporal Coherence for Compressible Neural Representations for Videos (opens in a new tab)
- CVPR (T1)UPLiFT: Efficient Pixel-Dense Feature Upsampling with Local Attenders (opens in a new tab)
- ICRA (T1)VeriGraph: Scene Graphs for Execution Verifiable Robot Planning (opens in a new tab)
- ECCV (T1)VidParse: Online Parsing of Egocentric Procedures Like a Pro (opens in a new tab)
202510 papers
- WACVA Video is Worth 10,000 Words: Training and Benchmarking with Diverse Captions for Better Long Video Retrieval (opens in a new tab)
- CVPR (T1)CoLLM: A Large Language Model for Composed Image Retrieval (opens in a new tab)
- CoRL (T1)Imagine, Verify, Execute: Memory-guided Agentic Exploration with Vision-Language Models (opens in a new tab)
- ICLR (T1)LARP: Tokenizing Videos with a Learned Autoregressive Generative Prior (opens in a new tab)
- MemVis Workshop, ICCVMAPS: Memory Augmented Panoptic Segmentation (opens in a new tab)
- FGVC Workshop, CVPRMulti-entity Video Transformers for Fine-Grained Video Representation Learning (opens in a new tab)
- ICRA (T1)P3-PO: Prescriptive Point Priors for Visuo-Spatial Generalization of Robot Policies (opens in a new tab)
- ICRA (T1)TREND: Tri-teaching for Robust Preference-based Reinforcement Learning with Demonstrations (opens in a new tab)
- ICCV (T1)Trokens: Semantic-Aware Relational Trajectory Tokens for Few-Shot Action Recognition (opens in a new tab)
- WACVUnified Framework for Open-World Compositional Zero-shot Learning (opens in a new tab)
202432 papers
- LPVL Workshop, CVPRAgglomerative Clustering of Atomic Actions for Unsupervised Action Segmentation
- IROS (T1)ARDuP: Active Region Video Diffusion for Universal Policies (opens in a new tab)
- Findings of EMNLPAutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models (opens in a new tab)
- CVPR (T1)Beyond Seen Primitive Concepts and Attribute-Object Compositional Learning (opens in a new tab)
- Nature Machine Intelligence (T1)Challenges, Evaluation and Opportunities for Open-World Learning (opens in a new tab)
- T-CAP Workshop, ECCVCoarse to Fine Human Mesh Recovery with Transformers (opens in a new tab)
- CVPR (T1)Composing Object Relations and Attributes for Image-Text Matching (opens in a new tab)
- WACVContent-Aware Image Color Editing with Auxiliary Color Restoration Tasks (opens in a new tab)
- ECCV (T1)Customize-A-Video: One-Shot Motion Customization of Text-to-Video Diffusion Models (opens in a new tab)
- WACVDiff2Lip: Audio Conditioned Diffusion Models for Lip-Synchronization (opens in a new tab)
- ECCV (T1)Do text-free diffusion models learn discriminative visual representations? (opens in a new tab)
- ECCV (T1)EAGLES: Efficient Accelerated 3D Gaussians with Lightweight EncodingS (opens in a new tab)
202318 papers
- BMVCA Frequency Perspective of Adversarial Robustness (opens in a new tab)
- CVPR (T1)Align and Attend: Multimodal Summarization with Dual Contrastive Losses (opens in a new tab)
- ICCV (T1)ASIC: Aligning Sparse in-the-wild Image Collections (opens in a new tab)
- ICCV (T1)BT2: Backward-compatible Training with Basis Transformation (opens in a new tab)
- ICCV (T1)Chop & Learn: Recognizing and Generating Object-State Compositions (opens in a new tab)
- EACLCOVID-VTS: Fact Extraction and Verification on Short Video Platforms
- CVPR (T1)FlexNeRF: Photorealistic Free-viewpoint Rendering of Moving Humans from Sparse Views (opens in a new tab)
- CVPR (T1)HNeRV: A Hybrid Neural Representation for Videos (opens in a new tab)
- ICLR (T1)LilNetX: Lightweight Networks with EXtreme Model Compression and Structured Sparsification (opens in a new tab)
- ICCV (T1)MOST: Multiple Object Localization with Self-Supervised Transformers for Object Discovery (opens in a new tab)
- CVPR (T1)NIRVANA: Neural Implicit Representations of Videos with Adaptive Networks and Autoregressive Patch-wise Modeling (opens in a new tab)
- Springer Book ChapterNovelty in Image Classification
Where alumni went31 listed, 74% to industry
Industry 17Academia 6
Most often to
- Amazon
- Meta
- Luma AI
Also to
- Institute of Foundation Models
Apply to UMDFall 2027
Not announced yet
UMD Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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